Search the World's Largest Database of Information Science & Technology Terms & Definitions
InfInfoScipedia LogoScipedia
A Free Service of IGI Global Publishing House
Below please find a list of definitions for the term that
you selected from multiple scholarly research resources.

What is Deep Learning

Chapter 3
AI-Enabled Social Robotics in Human Care Services
Deep learning is a subset of machine learning that involves the use of artificial neural networks with multiple layers to process and analyze data. Deep learning algorithms are designed to automatically learn representations of data through the use of multiple layers of artificial neurons, each layer building upon the previous one to create more complex and abstract representations.
Published in Chapter:
Learning Framework for Real-World Facial Emotion Recognition
Rohan Appasaheb Borgalli (Fr. Conceicao Rodrigues College of Engineering, India) and Sunil Surve (Fr. Conceicao Rodrigues College of Engineering, India)
Copyright: © 2023 |Pages: 32
DOI: 10.4018/978-1-6684-8171-4.ch003
Abstract
Facial expression recognition (FER) is an important research area in the fields of computer vision and artificial intelligence due to its application in academics as well as in industry. Research shows that using facial images/videos for recognition of facial expression is better because visual expressions carry major information through which emotions can be conveyed. Past research on FER has focused on the study of seven basic emotions; however, many more facial expressions are exhibited by humans that are considered compound emotions. State of art results shows machine learning and deep learning-based approaches are powerful over conventional FER approaches. This chapter focuses on surveying past work done in the field of real-world compound facial emotion recognition and implementing various learning frameworks such as machine learning and deep learning for real-world facial emotion recognition systems for detecting compound emotion using the facial expression image dataset RAF-DB for a real wild scenario.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Chapter 16
A Study on Deep Learning Methods in the Concept of Digital Industry 4.0
Deep learning is an artificial neural network technique with hidden layers.
Published in Chapter: A Study on Deep Learning Methods in the Concept of Digital Industry 4.0; From: Handbook of Research on Management and Strategies for Digital Enterprise Transformation
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Implementation of Different Machine Learning Projects Using Scikit-learn and Tensorflow Frameworks
It is an advanced version of artificial neural networks from machine learning techniques.
Published in Chapter: Implementation of Different Machine Learning Projects Using Scikit-learn and Tensorflow Frameworks; From: Methodologies, Frameworks, and Applications of Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 15
Performance Analysis of GAN Architecture for Effective Facial Expression Synthesis
A subset of a broader family of machine learning methods that makes use of multiple layers to extract data from raw input in order to learn its features.
Published in Chapter: Performance Analysis of GAN Architecture for Effective Facial Expression Synthesis; From: Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Artificial Intelligence Based on IoT for Healthcare
A sophisticated form of machine learning with the aim of self-directed information processing that creates nested hierarchical models for data processing and analysis, such as in image recognition or natural language processing.
Published in Chapter: Artificial Intelligence Based on IoT for Healthcare; From: AI-Enabled Multiple-Criteria Decision-Making Approaches for Healthcare Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Leveraging Technologies to Promote Clarity in Learning During the COVID-19 Pandemic: A Case Study
Learning that allows students to be actively engaged, involved, and part of their own learning.
Published in Chapter: Leveraging Technologies to Promote Clarity in Learning During the COVID-19 Pandemic: A Case Study; From: Cases on Innovative and Successful Uses of Digital Resources for Online Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
The Role of Artificial Intelligence in Cyber Security
The ability for machines to autonomously mimic human thought patterns through artificial neural networks composed of cascading layers of information.
Published in Chapter: The Role of Artificial Intelligence in Cyber Security; From: Countering Cyber Attacks and Preserving the Integrity and Availability of Critical Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 139
Malware Detection in Network Flows With Self-Supervised Deep Learning
Deep learning refers to a subset of the field of machine learning that utilizes a type of neural network algorithm that utilizes successive layers of neurons called perceptrons for the purpose of representation learning. The learning conducted by these various forms of neural networks can be either supervised, semi-supervised or unsupervised machine learning.
Published in Chapter: Malware Detection in Network Flows With Self-Supervised Deep Learning; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 24
How Can Education Use Artificial Intelligence?: A Brief History of AI, Its Usages, Its Successes, and Its Problems When Applied to Education.
Is a kind of ML where multiple layers of Neural Networks interconnected are used. It has proven in last years that the accuracy of predictions greatly improves.
Published in Chapter: How Can Education Use Artificial Intelligence?: A Brief History of AI, Its Usages, Its Successes, and Its Problems When Applied to Education.; From: Handbook of Research on Teaching With Virtual Environments and AI
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 14
Artificial Intelligence in Higher Education: A New Horizon
Artificial neural networks, a class of algorithms inspired by the structure and operation of the brain, are the focus of the machine learning discipline known as deep learning.
Published in Chapter: Artificial Intelligence in Higher Education: A New Horizon; From: Handbook of Research on AI Methods and Applications in Computer Engineering
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Deep Learning for Sentiment Analysis: An Overview and Perspectives
A form of machine learning which uses multi-layered architectures to automatically learn complex representations of the input data. Deep models deliver state-of-the-art results across many fields, e.g. computer vision and NLP.
Published in Chapter: Deep Learning for Sentiment Analysis: An Overview and Perspectives; From: Natural Language Processing for Global and Local Business
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Freshness Grading of Agricultural Products Using Artificial Intelligence
Deep learning is the subset of artificial intelligence and machine learning. Deep learning is used for processing meaningful data with various algorithms to teach computers actions of human intelligence.
Published in Chapter: Freshness Grading of Agricultural Products Using Artificial Intelligence; From: Artificial Intelligence Applications in Agriculture and Food Quality Improvement
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Using Gamification to Engage Higher-Order Thinking Skills
Deep learning is a level of learning that reflects an individuals’ commitment to learning for the purposes of subject mastery, demonstrated by application and integration in future learning endeavors.
Published in Chapter: Using Gamification to Engage Higher-Order Thinking Skills; From: Handbook of Research on Promoting Higher-Order Skills and Global Competencies in Life and Work
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Reframing Assessments: Designing Authentic Assessments in the Age of Generative AI
A subset of machine learning that uses artificial neural networks with multiple layers to analyse and process complex patterns in data.
Published in Chapter: Reframing Assessments: Designing Authentic Assessments in the Age of Generative AI; From: Academic Integrity in the Age of Artificial Intelligence
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Smart Agriculture Services Using Deep Learning, Big Data, and IoT (Internet of Things)
A sub branch of Artificial intelligence in which we built the DL model and we don’t need to specify any feature to the learning model . In case of DL the model will classify the data based on the input data.
Published in Chapter: Smart Agriculture Services Using Deep Learning, Big Data, and IoT (Internet of Things); From: Smart Agricultural Services Using Deep Learning, Big Data, and IoT
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Harnessing the Power of Machine Learning for Parkinson's Disease Detection
Deep learning is an extension of machine learning that makes use of artificial neural networks to simulate how the human brain learns.
Published in Chapter: Harnessing the Power of Machine Learning for Parkinson's Disease Detection; From: AIoT and Smart Sensing Technologies for Smart Devices
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
AI-Driven Big Healthcare Analytics: Contributions and Challenges
A specific part of machine learning models that employs multiple neural layers to solve more complex problems.
Published in Chapter: AI-Driven Big Healthcare Analytics: Contributions and Challenges; From: Intelligent Analytics With Advanced Multi-Industry Applications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
Towards an Anti-Racist, Culturally Responsive, and LGBTQ+ Inclusive Education: Developing Critically-Conscious Educational Leaders
Learning that lasts through the linking of knowledge and lived experiences in ways that encourage humans to see things differently.
Published in Chapter: Towards an Anti-Racist, Culturally Responsive, and LGBTQ+ Inclusive Education: Developing Critically-Conscious Educational Leaders; From: Cases on Academic Program Redesign for Greater Racial and Social Justice
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 14
Artificial Intelligence a Driver for Digital Transformation
Is a sub-discipline of machine learning that utilizes artificial neural network configured across multiple layers.
Published in Chapter: Artificial Intelligence a Driver for Digital Transformation; From: Handbook of Research on Digital Transformation and Challenges to Data Security and Privacy
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Lightweight ConvNet Model for American Sign Language Hand Gesture Recognition
Deep learning is a sort of machine learning and artificial intelligence that mimics how humans acquire knowledge. Data science, which covers statistics and predictive modelling, incorporates deep learning as a key component.
Published in Chapter: Lightweight ConvNet Model for American Sign Language Hand Gesture Recognition; From: Challenges and Applications for Hand Gesture Recognition
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Using Deep Learning and Big Data Analytics for Managing Cyber-Attacks
According to an article of Forbes , deep learning comes under the umbrella of Machine Learning where Artificial neural networks and various algorithms are inspired by the human brain and learn from enormous volumes of data.
Published in Chapter: Using Deep Learning and Big Data Analytics for Managing Cyber-Attacks; From: New Approaches to Data Analytics and Internet of Things Through Digital Twin
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Accessing Learning Management Systems With Smartphones: What Is the Effect on Learning Behavior and Student Engagement?
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
The Role of Big Data Analytics in Drug Discovery and Vaccine Development Against COVID-19
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: The Role of Big Data Analytics in Drug Discovery and Vaccine Development Against COVID-19; From: Applied Big Data Analytics and Its Role in COVID-19 Research
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Marketing and Artificial Intelligence: Personalization at Scale
Another term for unsupervised learning that includes reinforcement learning in which the machine responds to reaching goals given input data and constraints. Deep learning deals with multiple layers simulating neural networks with ability to process immense amount of data.
Published in Chapter: Marketing and Artificial Intelligence: Personalization at Scale; From: Handbook of Research on Applied AI for International Business and Marketing Applications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Model Optimisation Techniques for Convolutional Neural Networks
A recent branch of machine learning based on neural network architectures that are modelled after the human brain. Deep learning provides excellent results for computer vision, natural language processing, etc.
Published in Chapter: Model Optimisation Techniques for Convolutional Neural Networks; From: Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 17
Learning by Doing in 3D Environments: Collaborative Efforts in Second Life and Open Sim
Learning by problem solving, especially complex problems, as opposed to surface learning or rote learning.
Published in Chapter: Learning by Doing in 3D Environments: Collaborative Efforts in Second Life and Open Sim; From: Handbook of Research on Collaborative Teaching Practice in Virtual Learning Environments
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Heart Disease Diagnosis: A Machine Learning Approach
It is class of one machine learning algorithms that can be supervised, unsupervised, or semi-supervised. It uses multiple layers of processing units for feature extraction and transformation.
Published in Chapter: Heart Disease Diagnosis: A Machine Learning Approach; From: Advanced Classification Techniques for Healthcare Analysis
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Privacy-Preserving Machine Learning Techniques for IoT Data in Cloud Environments
Deep learning is a subfield of machine learning that focuses on teaching computers to learn and make decisions in a way inspired by the human brain. It uses artificial neural networks, which are computational models composed of interconnected nodes called “neurons.” These neural networks are structured in multiple layers, hence the term “deep” learning.
Published in Chapter: Privacy-Preserving Machine Learning Techniques for IoT Data in Cloud Environments; From: Emerging Technologies for Securing the Cloud and IoT
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Android-Based Skin Cancer Recognition System Using Convolutional Neural Network
It is an advanced version of artificial neural networks from machine learning techniques.
Published in Chapter: Android-Based Skin Cancer Recognition System Using Convolutional Neural Network; From: Diagnostic Applications of Health Intelligence and Surveillance Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Empowering Health With an Advanced Multi-Disease Prediction System and Medical Encyclopaedia: Apna Clinic
Deep learning is a subfield of machine learning that focuses on training artificial neural networks to learn and make predictions or decisions on their own. It is inspired by the structure and function of the human brain, specifically its interconnected network of neurons. Deep learning algorithms are designed to automatically learn representations of data through multiple layers of interconnected artificial neurons, also known as artificial neural networks. These networks have an input layer, one or more hidden layers, and an output layer. Each layer consists of multiple neurons that perform mathematical computations on the input data.
Published in Chapter: Empowering Health With an Advanced Multi-Disease Prediction System and Medical Encyclopaedia: Apna Clinic; From: Intelligent Engineering Applications and Applied Sciences for Sustainability
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 4
Behavior Classification of Egyptian Fruit Bat (Rousettus aegyptiacus) From Calls With Deep Learning
Is a class of broader machine learning algorithms which uses multiple layers to gradually extract higher-level features from the raw input data.
Published in Chapter: Behavior Classification of Egyptian Fruit Bat (Rousettus aegyptiacus) From Calls With Deep Learning; From: Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 4
How Artificial Intelligence Can Enhance Predictive Maintenance in Smart Factories
It refers to networks capable of learning unsupervised from data that is unstructured or unlabeled. It is also known as deep neural learning. It is seen as a subset of Machine Learning in Artificial Intelligence.
Published in Chapter: How Artificial Intelligence Can Enhance Predictive Maintenance in Smart Factories; From: Empowering Sustainable Industrial 4.0 Systems With Machine Intelligence
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Big Data Technologies and Pharmaceutical Manufacturing
A subtype of machine learning that refers to tools such as Artificial Neural Networks (ANN). These tools are trained to make decisions such as classifications or speech recognition. These are considered to be related to big data because the datasets required to train and verify the algorithms commonly fall into the general definition of big data.
Published in Chapter: Big Data Technologies and Pharmaceutical Manufacturing; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
The Use of Artificial Intelligence in the Food Industry: From Recipe Generation to Quality Control
DL is a subset of machine learning that utilizes artificial neural networks to model and train these networks on large datasets, allowing them to learn patterns and make predictions or classifications and solve complex problems.
Published in Chapter: The Use of Artificial Intelligence in the Food Industry: From Recipe Generation to Quality Control; From: Impactful Technologies Transforming the Food Industry
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Generation of Novel Synthetic Portable Chest X-Ray Images for Automatic COVID-19 Screening
Type of machine learning strategies that allows to create powerful classification and regression models able to deal directly with raw data.
Published in Chapter: Generation of Novel Synthetic Portable Chest X-Ray Images for Automatic COVID-19 Screening; From: AI Applications for Disease Diagnosis and Treatment
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 4
Machine Learning-Enhanced Text Mining as a Support Tool for Research on Climate Change: Theoretical and Technical Considerations
Deep learning is a subfield of machine learning. Deep neural networks (DNNs) are the extension of artificial neural networks (ANNs). Deep learning methods and techniques scale up the size and complexity of ANNs to produce increasingly richer functionality and very often archive better results in disciplines such as text mining or computer vision.
Published in Chapter: Machine Learning-Enhanced Text Mining as a Support Tool for Research on Climate Change: Theoretical and Technical Considerations; From: 5G, Artificial Intelligence, and Next Generation Internet of Things: Digital Innovation for Green and Sustainable Economies
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 169
Information-Rich Learning Concepts
Learning that goes beyond the bare minimum. Deep learners come to understand rather than simply to know the subject matter, and are able to make valid generalisations based on it.
Published in Chapter: Information-Rich Learning Concepts; From: Encyclopedia of Distance Learning, Second Edition
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 15
Big Data Application of Breast Cancer Prediction: A Healthcare 5.0 Application for Smart Cities
Deep learning is an advanced branch of artificial intelligence (AI) that aims to create intelligent computer systems capable of learning and decision-making. It draws inspiration from the human brain's structure and function, particularly its network of interconnected neurons. By utilizing artificial neural networks with multiple layers, deep learning algorithms can analyze vast amounts of data, identify meaningful patterns, and make predictions.
Published in Chapter: Big Data Application of Breast Cancer Prediction: A Healthcare 5.0 Application for Smart Cities; From: Pioneering Smart Healthcare 5.0 with IoT, Federated Learning, and Cloud Security
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Recent Trends in Deepfake Detection
It is an artificial intelligence (AI) technique for decision making by mimicking the human brain function for pattern discovery and data processing.
Published in Chapter: Recent Trends in Deepfake Detection; From: Deep Natural Language Processing and AI Applications for Industry 5.0
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Smart Diagnostics of COVID-19 With Data-Driven Approaches
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: Smart Diagnostics of COVID-19 With Data-Driven Approaches; From: Applied Big Data Analytics and Its Role in COVID-19 Research
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
Explainable Artificial Intelligence for Diagnosis of Cardiovascular Disease
By using neural networks to simulate human intellect, these algorithms seek to produce results that resemble those of the model.
Published in Chapter: Explainable Artificial Intelligence for Diagnosis of Cardiovascular Disease; From: Improving Security, Privacy, and Connectivity Among Telemedicine Platforms
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Investigation on Deep Learning Approach for Big Data: Applications and Challenges
It is a part of machine learning approach used for learning data representations.
Published in Chapter: Investigation on Deep Learning Approach for Big Data: Applications and Challenges; From: Handbook of Research on Pattern Engineering System Development for Big Data Analytics
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
EarLocalizer: A Deep-Learning-Based Ear Localization Model for Side Face Images in the Wild
A subbranch of machine learning which inspires from the artificial neural network. It has eliminated the need to design handcrafted features as in deep learning features are automatically learned by the model from the data.
Published in Chapter: EarLocalizer: A Deep-Learning-Based Ear Localization Model for Side Face Images in the Wild; From: Design and Implementation of Healthcare Biometric Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
Identifying COVID-19 Cases Rapidly and Remotely Using Big Data Analytics
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: Identifying COVID-19 Cases Rapidly and Remotely Using Big Data Analytics; From: Applied Big Data Analytics and Its Role in COVID-19 Research
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 18
The Pedagogical Potential of Design Thinking for CLIL Teaching: Creativity, Critical Thinking, and Deep Learning
In contradistinction to surface or superficial learning, deep learning is inextricably associated with long-term retention of pertinent and solid knowledge, based on a thorough and critical understanding of the object of study, be it curricular content or not.
Published in Chapter: The Pedagogical Potential of Design Thinking for CLIL Teaching: Creativity, Critical Thinking, and Deep Learning; From: Handbook of Research on Bilingual and Intercultural Education
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Piloting Artificial Intelligence (AI) to Facilitate Online Discussion in Large Online Classes: A Case Study
An education strategy focused on student mastery of foundational principles, theories, issues, problems, or concepts.
Published in Chapter: Piloting Artificial Intelligence (AI) to Facilitate Online Discussion in Large Online Classes: A Case Study; From: Cases on Innovative and Successful Uses of Digital Resources for Online Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Evolution and Tendency on the Feature Extraction Process for Diagnostic Aid in Healthcare
Part of machine learning which consists of the use of neural networks with three or more layers that allow learning from large amounts of data.
Published in Chapter: Evolution and Tendency on the Feature Extraction Process for Diagnostic Aid in Healthcare; From: Recent Advancements in Smart Remote Patient Monitoring, Wearable Devices, and Diagnostics Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Deep Learning in Retinal Diseases Diagnosis: A Review
A type of an artificial neural network with high degree of layers.
Published in Chapter: Deep Learning in Retinal Diseases Diagnosis: A Review; From: Machine Learning and AI Techniques in Interactive Medical Image Analysis
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 13
The Impact of News on Public-Private Partnership Stock Price in China via Text Mining Method
It is a data-based learning algorithm based on artificial neural networks. Deep learning is an algorithm that represents learning based on data in ML.
Published in Chapter: The Impact of News on Public-Private Partnership Stock Price in China via Text Mining Method; From: Intelligent Analytics With Advanced Multi-Industry Applications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 13
A Multifaceted Machine Learning Approach to Understand Road Accident Dynamics Using Twitter Data
Deep learning is a subfield of machine learning inspired by the human brain's structure and function, specifically the neural networks. It refers to artificial neural networks (ANN) with multiple layers, that is, architectures with more than one layer between input and output.
Published in Chapter: A Multifaceted Machine Learning Approach to Understand Road Accident Dynamics Using Twitter Data; From: Handbook of Research on Advancements of Contactless Technology and Service Innovation in Library and Information Science
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 21
A Literature Review on Thyroid Hormonal Problems in Women Using Data Science and Analytics: Healthcare Applications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Intelligent System for Predicting Healthcare Readmissions
Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data
Published in Chapter: Intelligent System for Predicting Healthcare Readmissions; From: Analyzing Current Digital Healthcare Trends Using Social Networks
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Ethical Considerations and Challenges in Neurodegenerative Diseases Using Machine Learning
Deep learning is a subset of machine learning where artificial neural networks with multiple layers (deep neural networks) learn intricate patterns from large datasets, allowing for complex tasks such as image and speech recognition.
Published in Chapter: Ethical Considerations and Challenges in Neurodegenerative Diseases Using Machine Learning; From: Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 30
Responsible Machine Learning for Ethical Artificial Intelligence in Business and Industry
A subset of machine learning in which an AI prepares a multilayer neural network of algorithms to build and constantly refine a prediction model based on available data (may be structured or unstructured).
Published in Chapter: Responsible Machine Learning for Ethical Artificial Intelligence in Business and Industry; From: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 76
Embodied Conversation: A Personalized Conversational HCI Interface for Ambient Intelligence
Part of Machine Learning, where methods of higher complexity are used for training data representation.
Published in Chapter: Embodied Conversation: A Personalized Conversational HCI Interface for Ambient Intelligence; From: Encyclopedia of Organizational Knowledge, Administration, and Technology
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Implementation of Deep Learning Neural Network for Retinal Images
Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised.
Published in Chapter: Implementation of Deep Learning Neural Network for Retinal Images; From: Handbook of Research on Applications and Implementations of Machine Learning Techniques
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 14
Predicting Healthcare Readmissions Using Artificial Intelligence
Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data.
Published in Chapter: Predicting Healthcare Readmissions Using Artificial Intelligence; From: Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 132
An E-Portfolio Scheme of Flexible Online Learning
Learning that goes beyond a surface level and promotes the development of meta-cognition through communities of inquiry.
Published in Chapter: An E-Portfolio Scheme of Flexible Online Learning; From: Encyclopedia of Distance Learning, Second Edition
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Immersive Technology: Past, Present, and Future in Education
Deep learning is associated with learning activities such as interacting with content, understanding and reasoning with materials, along with applying and transferring knowledge to new learning situations.
Published in Chapter: Immersive Technology: Past, Present, and Future in Education; From: Cognitive and Affective Perspectives on Immersive Technology in Education
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
A Survey on Intelligence Tools for Data Analytics
Sub-domain in the field of machine learning that deals with the use of algorithms inspired by human brain cells to solve complex real-world problems.
Published in Chapter: A Survey on Intelligence Tools for Data Analytics; From: Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Optimizing WSNs for CPS Using Machine Learning Techniques
It is an artificial intelligence technology that imitates the role of the human brain in data processing and the development of decision-making patterns.
Published in Chapter: Optimizing WSNs for CPS Using Machine Learning Techniques; From: Artificial Intelligence Paradigms for Smart Cyber-Physical Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 12
Digital-Based Assessments for Higher-Order and Critical Thinking Skills in Higher Education
Learning styles that help students to secure meaning and solve complex problems and apply knowledge to new situation.
Published in Chapter: Digital-Based Assessments for Higher-Order and Critical Thinking Skills in Higher Education; From: Handbook of Research on Digital-Based Assessment and Innovative Practices in Education
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Pattern Analysis in Marine Data Classification and Recognition: A Plea for Ontologies
a type of artificial intelligence based on a network of artificial neurons inspired by the human brain.
Published in Chapter: Pattern Analysis in Marine Data Classification and Recognition: A Plea for Ontologies; From: Handbook of Research on Technological Advances of Library and Information Science in Industry 5.0
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
An Overview of Biomedical Image Analysis From the Deep Learning Perspective
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Detection of Diabetic Retinopathy With Mobile Application Using Deep Learning
It is a machine learning method using multiple layers of nonlinear processing units to extract features from data.
Published in Chapter: Detection of Diabetic Retinopathy With Mobile Application Using Deep Learning; From: Diagnostic Applications of Health Intelligence and Surveillance Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Digital Recognition of Breast Cancer Using TakhisisNet: An Innovative Multi-Head Convolutional Neural Network for Classifying Breast Ultrasonic Images
Deep learning is a subset of machine learning that models high-level abstractions in data by means of network architectures, which are composed of multiple nonlinear transformations.
Published in Chapter: Digital Recognition of Breast Cancer Using TakhisisNet: An Innovative Multi-Head Convolutional Neural Network for Classifying Breast Ultrasonic Images; From: Opportunities and Challenges in Digital Healthcare Innovation
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 125
Artificial Intelligence, Big Data, and Machine Learning in Industry 4.0
A specialized form (sub-field) of machine learning with a multitude of layers through which the data is transformed.
Published in Chapter: Artificial Intelligence, Big Data, and Machine Learning in Industry 4.0; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 12
Making Smart Cities Smarter: Role of AI in Smart Cities Application
A part of a broader family of machine learning methods based on learning data representations.
Published in Chapter: Making Smart Cities Smarter: Role of AI in Smart Cities Application; From: Exploring Ethical Dimensions of Environmental Sustainability and Use of AI
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Overview of Machine Learning Approaches for Wireless Communication
The method for solving problems that have more probabilistic calculations based on artificial neural networks.
Published in Chapter: Overview of Machine Learning Approaches for Wireless Communication; From: Next-Generation Wireless Networks Meet Advanced Machine Learning Applications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 84
Decision-Making Approaches for Airport Surrounding Traffic Management
A subset of machine learning based on artificial neural networks with more layers, which can improve the model performance significantly.
Published in Chapter: Decision-Making Approaches for Airport Surrounding Traffic Management; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Artificial Intelligence in Modern Medical Science: A Promising Practice
Basically a subset of machine learning, which is a branch of artificial intelligence. It involves training artificial neural networks with large datasets to identify patterns and make predictions or decisions based on the input data.
Published in Chapter: Artificial Intelligence in Modern Medical Science: A Promising Practice; From: Recent Developments in Machine and Human Intelligence
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 15
Comparative Study on ASD Identification Using Machine and Deep Learning
Deep learning is a kind of machine learning technique with automatic image interpretation and feature learning facility. The different deep learning algorithms are convolutional neural network (CNN), deep neural network (DNN), recurrent neural network (RNN), genetic adversarial networks (GAN), etc.
Published in Chapter: Comparative Study on ASD Identification Using Machine and Deep Learning; From: Interdisciplinary Approaches to Altering Neurodevelopmental Disorders
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 16
Use of Generative AI Tools to Facilitate Personalized Learning in the Flipped Classroom
Through the processing and analysis of multi-layer data in machine learning, complex data can be automatically analyzed.
Published in Chapter: Use of Generative AI Tools to Facilitate Personalized Learning in the Flipped Classroom; From: Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Systematic Literature Review: XAI and Clinical Decision Support
The “deep” in deep learning refers to the depth of the layers in a neural network. A neural network that consists of more than three layers, including input and output layers, can be considered a deep learning algorithm.
Published in Chapter: Systematic Literature Review: XAI and Clinical Decision Support; From: Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Subjective and Objective Assessment for Variation of Plant Nitrogen Content to Air Pollutants Using Machine Intelligence: Subjective and Objective Assessment
Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on artificial neural networks. Learning can be supervised, semi-supervised, or unsupervised.
Published in Chapter: Subjective and Objective Assessment for Variation of Plant Nitrogen Content to Air Pollutants Using Machine Intelligence: Subjective and Objective Assessment; From: Fuzzy Expert Systems and Applications in Agricultural Diagnosis
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Development Trends in Robotization and Artificial Intelligence
A type of machine learning based on the use of neural networks.
Published in Chapter: Development Trends in Robotization and Artificial Intelligence; From: The Strategies of Informing Technology in the 21st Century
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Influence of Multimedia and Cognitive Strategies in Deep and Surface Verbal Processing: A Verbal-Linguistic Intelligence Perspective
Deep learning refers to learning activities that the learner interacts with the content, engages in understanding and reasoning the material, and applies and transfers knowledge to new learning situations.
Published in Chapter: Influence of Multimedia and Cognitive Strategies in Deep and Surface Verbal Processing: A Verbal-Linguistic Intelligence Perspective; From: Examining Multiple Intelligences and Digital Technologies for Enhanced Learning Opportunities
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Smart System and Services Using Artificial Intelligence and Machine Learning Algorithms: Sky of AI
Artificial intelligence (AI) and machine learning techniques called deep learning model how people acquire specific types of information. Data science, which also encompasses statistics and predictive modelling, contains deep learning as a key component.
Published in Chapter: Smart System and Services Using Artificial Intelligence and Machine Learning Algorithms: Sky of AI; From: Applying Drone Technologies and Robotics for Agricultural Sustainability
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Intelligent Automation Using Machine and Deep Learning in Cybersecurity of Industrial IoT: CCTV Security and DDoS Attack Detection
It is a part of machine learning intended for learning form large amounts of data, as in the case of experience-based learning. It can be considered that feature engineering in deep learning-based models is partly left to the machine. In the case of artificial neural networks, deep neural networks are expected to have various layers within architectures for solving complex problems with higher accuracy compared to traditional machine learning. Moreover, high performance automatic results are expected without human intervention.
Published in Chapter: Intelligent Automation Using Machine and Deep Learning in Cybersecurity of Industrial IoT: CCTV Security and DDoS Attack Detection; From: Cyber Security of Industrial Control Systems in the Future Internet Environment
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Automatic Image Captioning Using Different Variants of the Long Short-Term Memory (LSTM) Deep Learning Model
A subfield of Machine learning that enables computers to learn and enhance themselves with the help of neural networks.
Published in Chapter: Automatic Image Captioning Using Different Variants of the Long Short-Term Memory (LSTM) Deep Learning Model; From: Deep Learning Research Applications for Natural Language Processing
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 39
Game-Based Learning with a Dialogic Teaching Approach: A Case of Deep Learning and the Use of SporeTM in A-Level Biology Lessons
An approach to learning in which learners gain a thorough understanding by making connections with previous knowledge and examining evidence.
Published in Chapter: Game-Based Learning with a Dialogic Teaching Approach: A Case of Deep Learning and the Use of SporeTM in A-Level Biology Lessons; From: Handbook of Research on Improving Learning and Motivation through Educational Games: Multidisciplinary Approaches
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Developing a Web-Based COVID-19 Fake News Detector With Deep Learning
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: Developing a Web-Based COVID-19 Fake News Detector With Deep Learning; From: Applied Big Data Analytics and Its Role in COVID-19 Research
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 14
A Framework for Integrating Artificial Intelligence Into Library and Information Science Curricula
Refers to techniques enable this automatic learning through the absorption of huge amounts of unstructured data such as text, images, or video.
Published in Chapter: A Framework for Integrating Artificial Intelligence Into Library and Information Science Curricula; From: Innovative Technologies for Enhancing Knowledge Access in Academic Libraries
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Forecasting Techniques for the Pandemic Trend of COVID-19
A subset of machine learning based on artificial neural networks with more layers, which can improve the model performance significantly.
Published in Chapter: Forecasting Techniques for the Pandemic Trend of COVID-19; From: Applied Big Data Analytics and Its Role in COVID-19 Research
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Application of Deep Learning in the Processing of the Aerospace System's Multispectral Images
Is a group of methods that allow multilayer computing models to work with data that has an abstraction hierarchy.
Published in Chapter: Application of Deep Learning in the Processing of the Aerospace System's Multispectral Images; From: Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Real-Time Detection of Cardiac Arrest Using Deep Learning
Deep learning is a type of machine learning and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge.
Published in Chapter: Real-Time Detection of Cardiac Arrest Using Deep Learning; From: AI-Enabled Multiple-Criteria Decision-Making Approaches for Healthcare Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Predictive Modelling for Financial Fraud Detection Using Data Analytics: A Gradient-Boosting Decision Tree
This is the branch of machine learning and artificial intelligence that extract knowledge about the processing of the image or quantitative data.
Published in Chapter: Predictive Modelling for Financial Fraud Detection Using Data Analytics: A Gradient-Boosting Decision Tree; From: Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Digital Transformation in Contemporary Organizations: Creativity and Innovation in the 4th Industrial Revolution
A system where relationship among input and output can be established through combinations of feature extraction and classification.
Published in Chapter: Digital Transformation in Contemporary Organizations: Creativity and Innovation in the 4th Industrial Revolution; From: Multidisciplinary Approaches in AI, Creativity, Innovation, and Green Collaboration
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Autonomous Navigation of Rovers Using ML and DL Techniques
These algorithms aim to achieve outcomes similar to those produced by the human intellect modelled using Neural Networks.
Published in Chapter: Autonomous Navigation of Rovers Using ML and DL Techniques; From: AI-Enabled Social Robotics in Human Care Services
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Building Intelligent Cities: Concepts, Principles, and Technologies
This is also a subset of AI where unstructured data is processed using layers of neural networks to identify, predict and detect patterns. Deep learning is used when there is a large amount of unlabeled data and problem is too complex to be solved using machine learning algorithms. Deep learning algorithms are used in computer vision and facial recognition systems.
Published in Chapter: Building Intelligent Cities: Concepts, Principles, and Technologies; From: Developing and Monitoring Smart Environments for Intelligent Cities
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Monitoring Social Distancing With Real-Time Detection and Tracking
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: Monitoring Social Distancing With Real-Time Detection and Tracking; From: Applied Big Data Analytics and Its Role in COVID-19 Research
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 58
Understanding Machine Learning Concepts
It refers to Artificial Neural Networks and related Machine Learning algorithms that uses multiple layers of neurons. It is seen as a subset of Machine Learning in Artificial Intelligence.
Published in Chapter: Understanding Machine Learning Concepts; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Artificial Intelligence and Marketing: Progressive or Disruptive Transformation? Review of the Literature
Deep learning is a subfield of machine learning that focuses on using artificial neural networks with multiple layers (hence “deep”) to learn from and make predictions or decisions based on large amounts of complex and diverse data. Unlike traditional neural networks, deep learning algorithms use multiple layers of interconnected nodes to process and analyze data, allowing them to learn and make decisions at a higher level of abstraction.
Published in Chapter: Artificial Intelligence and Marketing: Progressive or Disruptive Transformation? Review of the Literature; From: Confronting Security and Privacy Challenges in Digital Marketing
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Exploring the Possibilities of Artificial Intelligence and Big Data Techniques to Enhance Gamified Financial Services
Artificial Neural Networks and related Machine Learning algorithms that use multiple layers of neurons. It is seen as a subset of Machine Learning in Artificial Intelligence.
Published in Chapter: Exploring the Possibilities of Artificial Intelligence and Big Data Techniques to Enhance Gamified Financial Services; From: Next-Generation Applications and Implementations of Gamification Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 16
Design of a Real-Time-Integrated System Based on Stereovision and YOLOv5 to Detect Objects
Subset of machine learning aiming to process data with algorithms inspired by the human brain.
Published in Chapter: Design of a Real-Time-Integrated System Based on Stereovision and YOLOv5 to Detect Objects; From: Enhancing Performance, Efficiency, and Security Through Complex Systems Control
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 14
Artificial Intelligence in Education: Current Insights and Future Perspectives
A part of a broader family of machine learning methods based on learning data representations
Published in Chapter: Artificial Intelligence in Education: Current Insights and Future Perspectives; From: Handbook of Research on Learning in the Age of Transhumanism
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Artificial Intelligence Applications in Cybersecurity
This is part of machine learning that uses many receptors to have a more layered procedure of machine learning.
Published in Chapter: Artificial Intelligence Applications in Cybersecurity; From: Handbook of Research on AI Methods and Applications in Computer Engineering
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 25
Toward the 4th Agenda 2030 Goal: AI Support to Executive Functions for Inclusions
The ability for machines to autonomously mimic human thought patterns through artificial neural networks composed of cascading layers of information.
Published in Chapter: Toward the 4th Agenda 2030 Goal: AI Support to Executive Functions for Inclusions; From: Handbook of Research on Teaching With Virtual Environments and AI
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Integrating Knowledge-Driven and Data-Driven Methodologies for an Efficient Clinical Decision Support System
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 20
A Transfer Learning Approach for Smart Home Application Based on Evolutionary Algorithms
It is a sub-category of machine learning based on artificial neural networks.
Published in Chapter: A Transfer Learning Approach for Smart Home Application Based on Evolutionary Algorithms; From: Handbook of Research on AI Methods and Applications in Computer Engineering
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 36
How Artificial Intelligence Is Impacting Marketing?
Deep learning can be defined as a type of machine learning technique that teaches technological software to imitate the way humans learn.
Published in Chapter: How Artificial Intelligence Is Impacting Marketing?; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Artificial Intelligence Methods for Face Covering Detections
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: Artificial Intelligence Methods for Face Covering Detections; From: Applied Big Data Analytics and Its Role in COVID-19 Research
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Ethical Navigations: Adaptable Frameworks for Responsible AI Use in Higher Education
A function of AI that imitates the human brain by learning from how it structures and processes information to make decisions. Instead of relying on an algorithm that can only perform one specific task, this subset of machine learning can learn from unstructured data without supervision.
Published in Chapter: Ethical Navigations: Adaptable Frameworks for Responsible AI Use in Higher Education; From: Exploring the Ethical Implications of Generative AI
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 12
AI-Enabled Internet of Nano Things Methodology for Healthcare Information Management
Deep learning is a type of machine learning and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge. Deep learning is an important element of data science, which includes statistics and predictive modeling.
Published in Chapter: AI-Enabled Internet of Nano Things Methodology for Healthcare Information Management; From: AI-Enabled Multiple-Criteria Decision-Making Approaches for Healthcare Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
A Study on Deep Learning Methods in the Concept of Industry 4.0
Deep Learning is an artificial neural network technique with hidden layers.
Published in Chapter: A Study on Deep Learning Methods in the Concept of Industry 4.0; From: Applied AI and Multimedia Technologies for Smart Manufacturing and CPS Applications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 26
Data Science in Economics and Business: Roots and Applications
It structures algorithms in layers to create an artificial neural network that can learn and make an intelligent decisions on its own.
Published in Chapter: Data Science in Economics and Business: Roots and Applications; From: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
AI and Data Analytics for Market Research and Competitive Intelligence
Deep learning is a subfield of machine learning that focuses on teaching computers to learn and make decisions in a way inspired by the human brain. It uses artificial neural networks, which are computational models composed of interconnected nodes called “neurons.” These neural networks are structured in multiple layers, hence the term “deep” learning.
Published in Chapter: AI and Data Analytics for Market Research and Competitive Intelligence; From: AI and Data Analytics Applications in Organizational Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Technologies for Connected Government Implementation: Success Factors and Best Practices
Deep learning refers to artificial neural networks that mimic the workings of the human brain in the formation of patterns used in data processing and decision-making. Deep learning is a subset of machine learning. They are artificial intelligence networks capable of learning from unstructured or unlabeled data.
Published in Chapter: Technologies for Connected Government Implementation: Success Factors and Best Practices; From: Web 2.0 and Cloud Technologies for Implementing Connected Government
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 149
Group Leadership in Online Collaborative Learning
This phrase characterizes an approach to learning, and it is contrasted with “surface” learning. Someone who adopts a deep learning approach may find the subject of study intrinsically motivating or very engaging.
Published in Chapter: Group Leadership in Online Collaborative Learning; From: Encyclopedia of Distance Learning, Second Edition
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Technology-Enhanced Pedagogical Models to Learn Critical Citizenship at a South African University
knowledge generation processes that trigger deep reflection, critical inquiry and collaborative generation of information by students and for students.
Published in Chapter: Technology-Enhanced Pedagogical Models to Learn Critical Citizenship at a South African University; From: Handbook of Research on Educational Technology Integration and Active Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Natural Language Processing in Online Reviews
It is a subarea of machine learning, where the models are built using multiple layers of artificial neural networks for learning useful patterns from raw data.
Published in Chapter: Natural Language Processing in Online Reviews; From: Natural Language Processing for Global and Local Business
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Importance of Deep Learning Models in the Medical Imaging Field
A self-learning technique of machines that is inspired by the working of human brain.
Published in Chapter: Importance of Deep Learning Models in the Medical Imaging Field; From: Approaches and Applications of Deep Learning in Virtual Medical Care
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 18
Inspection of Power Line Insulators: State of the Art, Challenges, and Open Issues
Is part of machine learning methods based on artificial neural networks with representation learning.
Published in Chapter: Inspection of Power Line Insulators: State of the Art, Challenges, and Open Issues; From: Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Generative AI in Higher Education
A subset of machine learning involving layered neural networks. These networks can learn from large amounts of data and are particularly effective in tasks such as image and speech recognition.
Published in Chapter: Generative AI in Higher Education; From: The Role of Generative AI in the Communication Classroom
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Artificial Intelligence as a Tool for Hybrid Education
A subfield within machine learning that uses neural networks with multiple layers (deep) to analyze large data sets, recognize patterns, and make decisions.
Published in Chapter: Artificial Intelligence as a Tool for Hybrid Education; From: Promoting Quality Hybrid Learning Through Leadership and Educational Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 14
The Role of Big Data Research Methodologies in Describing Investor Risk Attitudes and Predicting Stock Market Performance: Deep Learning and Risk Tolerance
A subset of machine learning, this is an advanced type of machine learning. The technique outperforms other prediction methodologies because deep learning utilizes unsupervised data forms.
Published in Chapter: The Role of Big Data Research Methodologies in Describing Investor Risk Attitudes and Predicting Stock Market Performance: Deep Learning and Risk Tolerance; From: Handbook of Research on New Challenges and Global Outlooks in Financial Risk Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Emotion Detection and Classification Using Machine Learning Techniques
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Gamification Tools to Facilitate Student Learning Engagement in Higher Education: A Burden or Blessing?
A sub-set of machine learning in artificial intelligence (AI) with network capabilities supporting learning unsupervised from unstructured data.
Published in Chapter: Gamification Tools to Facilitate Student Learning Engagement in Higher Education: A Burden or Blessing?; From: Fostering Communication and Learning With Underutilized Technologies in Higher Education
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Machine Learning and Deep Learning for Big Data Analysis
Deep learning is a subfield of machine learning that uses neural networks with numerous layers (deep neural networks) to learn and represent complicated patterns in data.
Published in Chapter: Machine Learning and Deep Learning for Big Data Analysis; From: Big Data Analytics Techniques for Market Intelligence
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Learning With Immersive Technology: A Cognitive Perspective
Deep learning is associated with learning activities such as interacting with content, understanding and reasoning with materials, along with applying and transferring knowledge to new learning situations.
Published in Chapter: Learning With Immersive Technology: A Cognitive Perspective; From: Cognitive and Affective Perspectives on Immersive Technology in Education
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
The Future of Artificial Intelligence in Agricultural Field: A Bibliometric Analysis
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Introduction to Artificial Intelligence
Is a section of machine learning that uses numerous receptors of different network levels to learn new scenarios.
Published in Chapter: Introduction to Artificial Intelligence; From: Handbook of Research on AI Methods and Applications in Computer Engineering
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Artificial Intelligence in General
It is a branch of machine learning based on a set of algorithms that can be used to model high-level abstractions in data by using multiple processing layers with complex structure, or otherwise composed of multiple non-linear transformations.
Published in Chapter: Artificial Intelligence in General; From: Human Behavior and Another Kind in Consciousness: Emerging Research and Opportunities
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Active Learning Strategies in Higher Education in the Arab World
Deep learning (deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning.
Published in Chapter: Active Learning Strategies in Higher Education in the Arab World; From: Agricultural Education for Development in the Arab Countries
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 90
Machine Learning for Decision Support in the ICU
Deep learning is a subset of machine learning, which is a neural network imitating the structure of a human brain.
Published in Chapter: Machine Learning for Decision Support in the ICU; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Artificial Intelligence: Concepts and Notions
Deep learning is a type of machine learning that can process a wider range of data resources, requires less data preprocessing by humans, and can often produce more accurate results than traditional machine-learning approaches. In deep learning, interconnected layers of software-based calculators known as “neurons” form a neural network. The network can ingest vast amounts of input data and process them through multiple layers that learn increasingly complex features of the data at each layer. The network can then make a determination about the data, learn if its determination is correct, and use what it has learned to make determinations about new data. For example, once it learns what an object looks like, it can recognize the object in a new image (Source: https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/an-executives-guide-to-ai ).
Published in Chapter: Artificial Intelligence: Concepts and Notions; From: Responsible AI and Ethical Issues for Businesses and Governments
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Real-Time Object Detection in Video for Traffic Monitoring
A type of machine learning that uses neural networks to model and solve complex problems.
Published in Chapter: Real-Time Object Detection in Video for Traffic Monitoring; From: AI Tools for Protecting and Preventing Sophisticated Cyber Attacks
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Techniques and Methods That Help to Make Big Data the Simplest Recipe for Success
Also known as deep structured learning or hierarchical learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.
Published in Chapter: Techniques and Methods That Help to Make Big Data the Simplest Recipe for Success; From: Big Data Analytics for Entrepreneurial Success
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
A Lightweight CNN to Identify Cardiac Arrhythmia Using 2D ECG Images
It is a category of artificial intelligence that combines a variety of models that are fundamentally based on artificial neural networks.
Published in Chapter: A Lightweight CNN to Identify Cardiac Arrhythmia Using 2D ECG Images; From: AI Applications for Disease Diagnosis and Treatment
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 153
An Image-Based Ship Detector With Deep Learning Algorithms
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: An Image-Based Ship Detector With Deep Learning Algorithms; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 13
Reevaluating Factor Models: Feature Extraction of the Factor Zoo
Deep learning is a subfield of machine learning that uses artificial neural networks to predict, classify, and generate data.
Published in Chapter: Reevaluating Factor Models: Feature Extraction of the Factor Zoo; From: Recent Applications of Financial Risk Modelling and Portfolio Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 18
Identifying Patterns in Fresh Produce Purchases: The Application of Machine Learning Techniques
A type of machine learning based on artificial neural networks. It can be supervised, unsupervised, or semi-supervised, and it uses an artificial neural network with multiple layers between the input and output layers.
Published in Chapter: Identifying Patterns in Fresh Produce Purchases: The Application of Machine Learning Techniques; From: Handbook of Research on Big Data Clustering and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 14
A Comparison of Deep Learning Models in Time Series Forecasting of Web Traffic Data From Kaggle
Imitates the way humans gain knowledge for automating predictive analytics and can be abstracted as a combination of the physical structure of a multi-layer neural network with activation functions, objective functions, optimization algorithms, and various auxiliary functions.
Published in Chapter: A Comparison of Deep Learning Models in Time Series Forecasting of Web Traffic Data From Kaggle; From: Handbook of Research on Foundations and Applications of Intelligent Business Analytics
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 6
Is AI in Your Future?: AI Considerations for Scholarly Publishers
Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.
Published in Chapter: Is AI in Your Future?: AI Considerations for Scholarly Publishers; From: Transforming Scholarly Publishing With Blockchain Technologies and AI
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Usage of Auxiliary Systems and Artificial Intelligence in Home-Based Rehabilitation: A Review
A subgroup of machine learning, essentially composed of algorithms that use a neural network with three or more layers together with large amounts of data, attempting to simulate the learning capabilities of the human brain.
Published in Chapter: Usage of Auxiliary Systems and Artificial Intelligence in Home-Based Rehabilitation: A Review; From: Exploring the Convergence of Computer and Medical Science Through Cloud Healthcare
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
Eye Tracker: An Assistive Tool in Diagnosis of Autism Spectrum Disorder
A learning algorithm using a number of layers for extracting and learning feature hierarchies before providing an output for any input.
Published in Chapter: Eye Tracker: An Assistive Tool in Diagnosis of Autism Spectrum Disorder; From: Emerging Trends in the Diagnosis and Intervention of Neurodevelopmental Disorders
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Deep Learning Approach for Extracting Catch Phrases from Legal Documents
A sub-field of machine learning which is based on the algorithms and layers of artificial networks.
Published in Chapter: Deep Learning Approach for Extracting Catch Phrases from Legal Documents; From: Neural Networks for Natural Language Processing
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Open Challenges and Research Issues of XAI in Modern Smart Cities
A subfield of machine learning that uses artificial neural networks to learn patterns from large datasets.
Published in Chapter: Open Challenges and Research Issues of XAI in Modern Smart Cities; From: Advances in Explainable AI Applications for Smart Cities
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Automated Essay Scoring Using Deep Learning Algorithms
A subarea of machine learning, which adopts a deeper and more complex neural structure to reach state-of-the-art accuracy in a given problem. Commonly applied in machine learning areas, such as classification and prediction.
Published in Chapter: Automated Essay Scoring Using Deep Learning Algorithms; From: Handbook of Research on Modern Educational Technologies, Applications, and Management
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Deep Learning Approach for Detecting Customer Churn in Telecommunication Industry
Deep learning is a method for teaching computers to mimic human behaviour. Deep learning models can sometimes outperform humans in terms of accuracy.
Published in Chapter: Deep Learning Approach for Detecting Customer Churn in Telecommunication Industry; From: Social Customer Relationship Management (Social-CRM) in the Era of Web 4.0
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Can Artificial Intelligence and Big Data Improve Gamified Healthcare Services and Devices?
It refers to Artificial Neural Networks and related machine learning algorithms that uses using multiple layers of neurons. It is seen as a subset of machine learning in artificial intelligence.
Published in Chapter: Can Artificial Intelligence and Big Data Improve Gamified Healthcare Services and Devices?; From: Next-Generation Applications and Implementations of Gamification Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 22
The Evolution of AI and Its Transformative Effects on Computing: A Comparative Analysis
Deep learning is a subfield of machine learning that focuses on teaching computers to learn and make decisions in a way inspired by the human brain. It uses artificial neural networks, which are computational models composed of interconnected nodes called “neurons.” These neural networks are structured in multiple layers, hence the term “deep” learning.
Published in Chapter: The Evolution of AI and Its Transformative Effects on Computing: A Comparative Analysis; From: Intelligent Engineering Applications and Applied Sciences for Sustainability
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 4
Connecting Best Practices for Teaching International Students With Student Satisfaction: A Review of STEM and Non-STEM Student Perspectives
Learning that promotes deep understanding of content and facilitates active learning through applied educational experiences.
Published in Chapter: Connecting Best Practices for Teaching International Students With Student Satisfaction: A Review of STEM and Non-STEM Student Perspectives; From: Multidisciplinary Perspectives on International Student Experience in Canadian Higher Education
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
How Does AI Make Libraries Smart?: A Case Study of Hangzhou Public Library
Deep learning is a branch of machine that typically utilizes an artificial neural network for data representation learning. It is usually used for speech recognition and image classification.
Published in Chapter: How Does AI Make Libraries Smart?: A Case Study of Hangzhou Public Library; From: Technological Advancements in Library Service Innovation
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 12
Virtual Reality Applications as an Innovative Educational Practice in Adult Education: A Case Study on Training Hellenic Air Force Pilots
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 575
Applications of Artificial Neural Networks in Economics and Finance
A branch of machine learning to whose architectures belong deep ANNs. The term “deep” denotes the application of multiple layers with a complex structure.
Published in Chapter: Applications of Artificial Neural Networks in Economics and Finance; From: Encyclopedia of Information Science and Technology, Fourth Edition
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
A Survey on Network Intrusion Detection Using Deep Generative Networks for Cyber-Physical Systems
Deep learning is a compilation of algorithms used in machine learning, and used to model high-level abstractions in data through the use of model architectures.
Published in Chapter: A Survey on Network Intrusion Detection Using Deep Generative Networks for Cyber-Physical Systems; From: Artificial Intelligence Paradigms for Smart Cyber-Physical Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 89
Machine Learning Approach to Art Authentication
A type of machine learning which leverages a layered pipeline of neural networks which progressively extract features from input data.
Published in Chapter: Machine Learning Approach to Art Authentication; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
How Artificial Intelligence Can Help Accounting in Information Management
Machine learning technique that teaches computers to do what comes naturally to humans.
Published in Chapter: How Artificial Intelligence Can Help Accounting in Information Management; From: Artificial Intelligence Approaches to Sustainable Accounting
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 132
Reflection as a Process From Theory to Practice
Learning based on critical examination and understanding of new facts, theories and concepts by linking them with existing cognitive structures and knowledge.
Published in Chapter: Reflection as a Process From Theory to Practice; From: Encyclopedia of Information Science and Technology, Fourth Edition
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Predictions For COVID-19 With Deep Learning Models of Long Short-Term Memory (LSTM)
Deep learning, a subset of machine learning, utilizes a hierarchical level of Artificial Neural Networks to carry out the process of machine learning. It mimics the working of the human brain in processing supervised and unsupervised data in detecting objects, recognizing speech, translating languages, and making decisions.
Published in Chapter: Predictions For COVID-19 With Deep Learning Models of Long Short-Term Memory (LSTM); From: Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Develop a Neural Model to Score Bigram of Words Using Bag-of-Words Model for Sentiment Analysis
This method is also called as hierarchical learning or deep structured learning. It is one of the machine learning method that is based on learning methods like supervised, semi-supervised or unsupervised. The only difference between deep learning and other machine learning algorithm is that deep learning method uses big data as input.
Published in Chapter: Develop a Neural Model to Score Bigram of Words Using Bag-of-Words Model for Sentiment Analysis; From: Neural Networks for Natural Language Processing
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 4
Deeper Self-Directed Learning for the 21st Century and Beyond
To override past experiences and prior knowledge by adapting to new circumstances and providing creative and ground-breaking new ideas.
Published in Chapter: Deeper Self-Directed Learning for the 21st Century and Beyond; From: Self-Directed Learning and the Academic Evolution From Pedagogy to Andragogy
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 5
Applying Machine Learning to Online Data?: Beware! Computational Social Science Requires Care
A subfield of machine learning that works with artificial neural networks containing many hidden layers and complex structures.
Published in Chapter: Applying Machine Learning to Online Data?: Beware! Computational Social Science Requires Care; From: Opportunities and Challenges for Computational Social Science Methods
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Convergence of AI, ML, and DL for Enabling Smart Intelligence: Artificial Intelligence, Machine Learning, Deep Learning, Internet of Things
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Engineering AI Systems: A Research Agenda
One part of the broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.
Published in Chapter: Engineering AI Systems: A Research Agenda; From: Artificial Intelligence Paradigms for Smart Cyber-Physical Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
Deep Learning Applied to COVID-19 Detection in X-Ray Images
Deep Learning corresponds to a subset of Artificial Intelligence techniques that comprises models based on artificial neural networks.
Published in Chapter: Deep Learning Applied to COVID-19 Detection in X-Ray Images; From: AI Applications for Disease Diagnosis and Treatment
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Risk-Benefit Evaluation in Clinical Research Practice
Is the complex, unsupervised processing of unstructured data in order to create patterns used in decision making, patterns that are analogous to those of the human brain.
Published in Chapter: Risk-Benefit Evaluation in Clinical Research Practice; From: Ethics in Research Practice and Innovation
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Industrial Automation Using Mobile Cyber Physical Systems
A type of machine learning based on artificial neural networks in which several layers of processing happen that help in extracting higher level features of data.
Published in Chapter: Industrial Automation Using Mobile Cyber Physical Systems; From: Deep Learning Applications for Cyber-Physical Systems
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 18
Machine Learning in Text Analysis
An extension of machine learning approach, which uses neural network.
Published in Chapter: Machine Learning in Text Analysis; From: Handbook of Research on Emerging Trends and Applications of Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Cultural Markers and Their Impact on Teaching in Higher Education
Engaging the material to be learned for the purpose of understanding and mastering it. Finding multiple resources, seeking experts, exploring different concepts, and using active learning approaches are examples of deep learning.
Published in Chapter: Cultural Markers and Their Impact on Teaching in Higher Education; From: Handbook of Research on Cross-Cultural Online Learning in Higher Education
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
Internet of Things Application for Intelligent Cities: Security Risk Assessment Challenges
An artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making.
Published in Chapter: Internet of Things Application for Intelligent Cities: Security Risk Assessment Challenges; From: Developing and Monitoring Smart Environments for Intelligent Cities
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Achieving Ambient Intelligence in Addressing the COVID-19 Pandemic Using Fog Computing-Driven IoT
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 16
Efficient End-to-End Asynchronous Time-Series Modeling With Deep Learning to Predict Customer Attrition
A subfield of machine learning that specializes in neural network based algorithms that have more than one hidden layer.
Published in Chapter: Efficient End-to-End Asynchronous Time-Series Modeling With Deep Learning to Predict Customer Attrition; From: Handbook of Research on Methodologies and Applications of Supercomputing
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
The Future of Advertising: Influencing and Predicting Response Through Artificial Intelligence, Machine Learning, and Neuroscience
A subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network.
Published in Chapter: The Future of Advertising: Influencing and Predicting Response Through Artificial Intelligence, Machine Learning, and Neuroscience; From: Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 4
Cardiovascular Applications of Artificial Intelligence in Research, Diagnosis, and Disease Management
A class of machine learning based on artificial neural networks that include multiple hidden layers to progressively extract higher level features from the raw data.
Published in Chapter: Cardiovascular Applications of Artificial Intelligence in Research, Diagnosis, and Disease Management; From: Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 3
Understanding Convolutional Neural Network With TensorFlow: CNN
Deep Learning is a branch of artificial intelligence dealing with artificial neural network learning algorithms and brain function. These neural networks seek to imitate the activity of the human brain, though imperfectly, allowing them to “learn” from massive amounts of data.
Published in Chapter: Understanding Convolutional Neural Network With TensorFlow: CNN; From: Machine Learning Algorithms Using Scikit and TensorFlow Environments
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Comparing Big Data Analysis Techniques
A subset of machine learning used for performing complex tasks.
Published in Chapter: Comparing Big Data Analysis Techniques; From: Big Data Analytics Techniques for Market Intelligence
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 170
Reinforcement Learning for Combinatorial Optimization
A kind of machine learning technique teaches computers to do what comes naturally to humans.
Published in Chapter: Reinforcement Learning for Combinatorial Optimization; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 1
Computational Psychometrics Social Analysis of Learners in Their Learning Behaviour Using AI Algorithms
It is a subset of machine learning that utilizes neural networks to model complex patterns and relationships in data.
Published in Chapter: Computational Psychometrics Social Analysis of Learners in Their Learning Behaviour Using AI Algorithms; From: AI-Enabled Social Robotics in Human Care Services
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Impact of Artificial Intelligence on Marketing Research: Challenges and Ethical Considerations
A subset of machine learning that uses artificial neural networks with multiple layers to learn and extract features from complex data.
Published in Chapter: Impact of Artificial Intelligence on Marketing Research: Challenges and Ethical Considerations; From: Philosophy of Artificial Intelligence and Its Place in Society
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 21
Towards an Effective Imaging-Based Decision Support System for Skin Cancer
Subfield of machine learning that mimics the workings of the human brain in process of data analysis, interpretation and decision making.
Published in Chapter: Towards an Effective Imaging-Based Decision Support System for Skin Cancer; From: Handbook of Research on Applied Intelligence for Health and Clinical Informatics
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 12
Intelligent Tracking and Positioning of Targets Using Passive Sensing Systems
Deep learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised, or unsupervised.
Published in Chapter: Intelligent Tracking and Positioning of Targets Using Passive Sensing Systems; From: Next-Generation Wireless Networks Meet Advanced Machine Learning Applications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Emerging Technologies to Increase Energy Efficiency and Decrease Indoor Pollution in University Campuses
It refers to Artificial Neural Networks and related Machine Learning algorithms that uses using multiple layers of neurons. It is seen as a subset of Machine Learning in Artificial Intelligence.
Published in Chapter: Emerging Technologies to Increase Energy Efficiency and Decrease Indoor Pollution in University Campuses; From: Strategy, Policy, Practice, and Governance for AI in Higher Education Institutions
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 13
A Comprehensive Review on AI Techniques for Healthcare
It is a branch of machine learning which helps the computer to learn how to do activities like humans do.
Published in Chapter: A Comprehensive Review on AI Techniques for Healthcare; From: Revolutionizing Healthcare Through Artificial Intelligence and Internet of Things Applications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 4
Biometrics for Forensic Identification in Web Applications and Social Platforms Using Deep Learning
It is the broader family of machine learning which makes use of methods to learn features and representations from data, unlike task specific algorithm.
Published in Chapter: Biometrics for Forensic Identification in Web Applications and Social Platforms Using Deep Learning; From: Forensic Investigations and Risk Management in Mobile and Wireless Communications
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Big Data Helps for Non-Pharmacological Disease Control Measures of COVID-19
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: Big Data Helps for Non-Pharmacological Disease Control Measures of COVID-19; From: Encyclopedia of Data Science and Machine Learning
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 11
Fighting Anti-Asian Hate in and After the COVID-19 Crisis With Big Data Analytics
A broad family of machine learning models based on neural networks. Typical deep learning models are deep neural networks, convolutional neural networks, recurrent neural networks, deep belief networks, and deep reinforcement learning.
Published in Chapter: Fighting Anti-Asian Hate in and After the COVID-19 Crisis With Big Data Analytics; From: Applied Big Data Analytics and Its Role in COVID-19 Research
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Exploring Public Perceptions of COVID-19 Vaccine Adverse Effects Through Social Media Analysis
ML can be considered a subset of deep learning. The field relies on studying computer algorithms to learn and advance independently. Deep learning uses artificial neural networks created to simulate how humans think and learn, whereas machine learning uses simpler principles ( Nyawa, Tchuente, & Fosso-Wamba, 2022 ).
Published in Chapter: Exploring Public Perceptions of COVID-19 Vaccine Adverse Effects Through Social Media Analysis; From: Handbook of Research on Advancements of Contactless Technology and Service Innovation in Library and Information Science
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 17
Sustainable E-Waste Management: Present Situation, Emerging Solutions, and Future Trends
A part of a broader family of machine learning methods based on learning data representations.
Published in Chapter: Sustainable E-Waste Management: Present Situation, Emerging Solutions, and Future Trends; From: Sustainable Solutions for E-Waste and Development
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 10
An Exploration of Learner-Centered Professional Development for Reluctant Math Teachers
A framework of learning which utilizes learning tasks to harness the power of new learning partnerships. Individuals engage in practicing the process of deep learning through discovering and mastering existing knowledge, and creating and using new knowledge. Deep learning tasks are energized by the notion of ‘learning leadership’, in which students are expected to become leaders of their own learning, who are able to define and pursue their own learning goals, using the resources, tools, and connections that digital access enables.
Published in Chapter: An Exploration of Learner-Centered Professional Development for Reluctant Math Teachers; From: Handbook of Research on Learner-Centered Pedagogy in Teacher Education and Professional Development
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Deep Learning and Sustainable Telemedicine
Deep learning is a collection of algorithms used in machine learning, used to model high-level abstractions in data through the use of model architectures, which are composed of multiple nonlinear transformations. It is part of a broad family of methods used for machine learning that are based on learning representations of data.
Published in Chapter: Deep Learning and Sustainable Telemedicine; From: Impacts of Information Technology on Patient Care and Empowerment
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 7
Application of Deep Learning for EEG
Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled.
Published in Chapter: Application of Deep Learning for EEG; From: Handbook of Research on Advancements of Artificial Intelligence in Healthcare Engineering
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 9
Research Journey of Hate Content Detection From Cyberspace
Deep learning approach is a subfield of the machine learning technique. The concepts of deep learning influenced by neuron and brain structure based on ANN (Artificial Neural Network).
Published in Chapter: Research Journey of Hate Content Detection From Cyberspace; From: Natural Language Processing for Global and Local Business
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 2
Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0
Is a subset of AI and machine learning that uses multi-layered artificial neural networks to learn from data that is unstructured or unlabeled.
Published in Chapter: Intelligent Manufacturing Systems Driven by Artificial Intelligence in Industry 4.0; From: Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
Deep Learning for Facial Skin Issues Detection: A Study for Global Care With Healthcare 5.0
Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy.
Published in Chapter: Deep Learning for Facial Skin Issues Detection: A Study for Global Care With Healthcare 5.0; From: Federated Learning and AI for Healthcare 5.0
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 28
Open Source Software Usage in Education and Research: Network Traffic Analysis as an Example
A recent method of machine learning based on neural networks with more than one hidden layer.
Published in Chapter: Open Source Software Usage in Education and Research: Network Traffic Analysis as an Example; From: Handbook of Research on Engineering Education in a Global Context
Full Text Chapter Download: US $37.50 Add to Cart
Chapter 8
AI-Driven System for Early Detection and Diagnosis of Cataracts by Image Recognition and Machine Learning Algorithms
A subfield of machine learning known as “deep learning” makes use of multi-layered neural networks. Deep learning, which draws inspiration from the anatomy of the human brain, has played a pivotal role in accomplishing outstanding achievements in domains including autonomous vehicles, natural language processing, picture and audio recognition, and more ( Khang & Hajimahmud, 2024 ).
Published in Chapter: AI-Driven System for Early Detection and Diagnosis of Cataracts by Image Recognition and Machine Learning Algorithms; From: AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications
Full Text Chapter Download: US $37.50 Add to Cart
eContent Pro Discount Banner
InfoSci OnDemandECP Editorial ServicesAGOSR