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What is Neural Network

Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care
A network of mathematical neurons that simulate the human brain, therefore approximating the behavior of nonlinear systems.
Published in Chapter:
Image Based Classification Platform: Application to Breast Cancer Diagnosis
Paolo J. S. Gonçalves (Polytechnic Institute of Castelo Branco, Portugal & Technical University of Lisbon, Portugal), Rui J. Almeida (Erasmus University Rotterdam, The Netherlands), João R. Caldas Pinto (Technical University of Lisbon, Portugal), Susana M. Vieira (Technical University of Lisbon, Portugal), and João M. C. Sousa (Technical University of Lisbon, Portugal)
DOI: 10.4018/978-1-4666-3990-4.ch031
Abstract
The high number of exams that is done in healthcare institutions increases the medical doctors’ workload, leading to poor working conditions and the increase of wrong diagnoses. As consequence, an automatic system that can help medical doctors in diagnostic tasks is of major interest to any healthcare institution. The chapter proposes an Image Based Classification Platform suitable to help Medical Doctors diagnosing breast cancer, based on mammograms, i.e., to detect if a tumor is present in the image. The platform is twofold, i.e., in the first part the image descriptors are extracted from the image using image-processing algorithms. The obtained descriptors are used in the second part. The second part is related to classification, where computational intelligence methods are used to classify a given image, based on the descriptors obtained in the first phase. Texture analysis based on co-occurrence matrices are applied to obtain the descriptors from the MIAS database of mammograms. From these descriptors, fuzzy models, neural networks, and support vector machines are successfully used to classify the mammograms and obtain a diagnosis.
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Fall Detection Systems to be Used by Elderly People
A data structure based on the biological neural net used to represent knowledge inducted by example patterns about a given context.
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Image Based Classification Platform: Application to Breast Cancer Diagnosis
A network of mathematical neurons that simulate the human brain, therefore approximating the behavior of nonlinear systems.
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Protein Structure Prediction by Fusion,Bayesian Methods
A Neural Network is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems.
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A Complex Non-Contact Bio-Instrumental System
A system of programs and data structures that approximates the operation of the human brain.
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Board Games AI
A network consisting of several layers of nodes and connections with weights which models the information processing operation of the human brain. Neural networks are used in Machine Learning as universal function approximators.
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A Hybrid Computational Intelligence Algorithm to Transform Traditional IPC Into a Smart Camera
A set of algorithms to identify the relationship between collection of data available like human brain cognition.
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Contribution of Neural Networks in Different Applications
It is a system having functionality akin to the human brain. It incorporates and replicates some abilities of the human brain like the ability of learning.
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An Intelligent Wearable Platform for Real Time Pilot's Health Telemonitoring
A computing solution that is loosely modeled after cortical structures of the brain. It consists of interconnected processing elements called nodes or neurons that work together to produce an output function.
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Differential Learning Expert System in Data Management
A member of a class of software that is “trained” by presenting it with examples of input and the corresponding desired output. Training might be conducted using synthetic data, iterating on the examples until satisfactory depth estimates are obtained. Neural networks are general-purpose programs, which have applications outside potential fields, including almost any problem that can be regarded as pattern recognition in some form.
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Artificial Intelligence in Computer Science
An AI method known as a neural network trains computers to analyse data in a way that is modelled after the human brain.
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A Review of Vessel Segmentation Methodologies and Algorithms: Comprehensive Review
A Deep learning technology depends on simulating the nature of brain to solve pattern recognition problems.
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An Adaptive Path Planning Based on Improved Fuzzy Neural Network for Multi-robot Systems
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Skin Cancer Lesion Detection Using Improved CNN Techniques
A machine learning method is employed to aid with categorization issues. The neural network is also one of the techniques used for allocation and optimization.
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Incremental Neural Network Training for Medical Diagnosis
A network of interconnecting neurons working together to produce some output function. The working of a neural network relies on the cooperation of the individual neurons within the network.
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A Survey of Tasks Scheduling Algorithms in Distributed Computing Systems
Set of algorithms, modelled loosely after the human brain, that is designed to recognize patterns.
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The Artificial Intelligence in the Sphere of the Administrative Law
It is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain.
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Applications for Data Mining Techniques in Customer Relationship Management
A computational approach inspired by simple models of the brain, consisting of nodes or neurons connected together in some sort of network.
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Brain-Machine Interfaces: Advanced Issues and Approaches
The artificial intelligence method that emulates the application of human brain.
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Deep Learning Approach for Extracting Catch Phrases from Legal Documents
Fully connected network with minimum of three layers namely input layer, output layer and hidden layer.
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Artificial Intelligence Based on IoT for Healthcare
A computer architecture that can learn through a process of trial and error that connects multiple processors in a way that is like the connections between neurons in the human brain.
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The Educational and Academic Innovation of the Avionics Engineering Center
A computational model used in computer science and other research disciplines, which is based on a large collection of simple neural units (artificial neurons), loosely analogous to the observed behavior of a biological brain's axons.
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Sentiment Mining: A Data-Driven Approach for Optimizing Digital Marketing Strategies
A neural network is a computer program designed to learn and make decisions by simulating the way our brains work. It's a tool that can find patterns in data and use them to solve problems, like recognizing pictures, understanding language, or making predictions. Think of it as a digital brain that gets better at tasks as it practices and learns from examples.
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Natural Language Processing and Biological Methods
Interconnected group of artificial neurons that uses a mathematical or a computational model for information processing based on a connectionist approach to computation. It involves a network of simple processing elements that can exhibit complex global behaviour.
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Information System Architecture in Apparel Production for Maintaining Supply Chain Sustainability
Neural network is an information processing paradigm inspired by how biological nervous systems, such as the brain, process information. It uses a classification mechanism that is modelled after the brain and operates by modifying the input through weights to determine what it should output.
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Data Analytics in the Global Product Development Supply Chain
Neural network is an information processing paradigm inspired by how biological nervous systems, such as the brain, process information. It uses a classification mechanism that is modelled after the brain and operates by modifying the input through weights to determine what it should output.
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Methods for Reverse Engineering of Gene Regulatory Networks
This refers to a graphical structure with artificial neurons as nodes. The node value of each node is determined by the input signals of the connected nodes passing through a nonlinear transfer function.
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Bio-Medical Image Processing: Medical Image Analysis for Malaria With Deep Learning
A computer system modeled on the human brain and nervous system.
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Design of a Real-Time-Integrated System Based on Stereovision and YOLOv5 to Detect Objects
This is a network used in deep learning and inspired from the human brain architecture: It relies on several layers to teach the machine how to process data for different applications such as object detection.
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Toward the 4th Agenda 2030 Goal: AI Support to Executive Functions for Inclusions
Also called a neural net, this is a computer system designed to function like the human brain. Although researchers are still working on creating a machine model of the human brain, existing neural networks can perform many tasks involving speech, vision, and board game strategy.
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Evolutionary Computing Approaches to System Identification
Neural network is a soft computing paradigm inspired by the working of human brain to inculcate intelligence in machines.
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Visualizing Neuroscience Through AI: A Systematic Review
They are a component of deep learning algorithms modeled after brain activity, emulating how neurons communicate with one another.
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History of Artificial Intelligence
A computation system containing a set of connected elements to solve arithmetic problems. The basis of the neural network computation is to analyze how the brain works and simulate it.
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Explainable Deep Reinforcement Learning for Knowledge Graph Reasoning
A framework involves interconnected layers of weighted neurons, which is motived by the human brain.
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Deep Learning Applications in Agriculture: The Role of Deep Learning in Smart Agriculture
An artificial neural network is based on a simplification of neurons in an animal brain which is a group of interconnected neurons.
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Support of Online Learning through Intelligent Programs
An empirical learning program is one capable of learning from examples by a process of generalization. Empirical learning corresponds to giving a person a lot of examples without any explanation of why the examples are members of a particular class. Empirical learning systems inductively generalize specific examples. Artificial neural networks are a particular method for empirical learning. They have proven to be equal, or superior, to other empirical learning systems over a wide range of domains, when evaluated in terms of their generalization ability.
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How Can Education Use Artificial Intelligence?: A Brief History of AI, Its Usages, Its Successes, and Its Problems When Applied to Education.
A promising new AI technique involving trainable sets of simple nodes (neurons). The network can be instructed to produce an acceptable numerical output giving some defined numerical input. Since text, images and almost everything can be represented by numbers NN can be used to define Algorithms in implicit ways, giving examples of what to do instead of explicitly programming every step.
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Machine Intelligence Using Hierarchical Memory Networks
A network of neurons or a hardware or mathematical model that represents such a network.
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Impulse Noise Filtering: Review of the State-of-the-Art Algorithms for Impulse Noise Filtering
Neural network is a computational model built in accordance with the central nervous system of human being.
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RIP Technique for Frequent Itemset Mining
A neural network is a software (or hardware) simulation of a biological brain (sometimes called Artificial Neural Network or “ANN”). The purpose of a neural network is to learn to recognize patterns in your data. Once the neural network has been trained on samples of your data, it can make predictions by detecting similar patterns in future data.
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Deep Learning for Moving Object Detection and Tracking
It is a computing system with interconnected nodes that can recognize hidden patterns and their correlations in input data.
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Methods of Forecasting Solar Radiation
A method to predict temporal series with chaotic or irregular behavior
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Development Trends in Robotization and Artificial Intelligence
A network loosely modeled on biological neurons that is used in deep learning to automatically improve computer algorithms and processes.
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Recognising Human Behaviour in a Spatio-Temporal Context
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The Integrated Value Model (IVM): A Relational Data Model of Business Value
A group of nodes where each represents the relationship of component sources (in a row) in a crosswalk which have been depicted as a three-dimensional visualization. Each source has component constellations showing added value to components of other sources . See also value network .
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Using Graph Neural Network to Enhance Quality of Service Prediction
It is a subset of machine learning and is at the heart of deep learning algorithms. Its name and structure are inspired by the human brain, mimicking how biological neurons signal each other. Artificial Neural Networks consist of a node layer containing an input layer, one or more hidden layers, and an output layer. Each node, or artificial neuron, connects to another and has an associated weight and threshold. If the output of any individual node is higher than the specified threshold value, that node is activated, sending data to the next layer of the network. Otherwise, no data will be passed to the next layer of the network ( Janiesch et al., 2021 ).
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The Evolution of AI and Data Science
A Neural Network is an interconnected layered structure of multiple nodes or neurons, which enables the system to use information within these nodes or neurons simultaneously to analyze and process data.
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Is AI in Your Future?: AI Considerations for Scholarly Publishers
Artificial neural networks, usually simply called neural networks, are computing systems vaguely inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain.
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Reliability Modeling and Assessment for Open Source Cloud Software: A Stochastic Approach
The machine learning technique using the input-output rules learned from the data sets.
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A Review of Big Data Analytics for the Internet of Things Applications in Supply Chain Management
Neural network is an information processing paradigm inspired by how biological nervous systems, such as the brain, process information. It uses a classification mechanism that is modelled after the brain and operates by modifying the input through weights to determine what it should output.
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Modeling of Uncertain Nonlinear System With Z-Numbers
A neural network is a set of layers (a layer has set of neurons) stacked together sequentially.
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Mispronunciation Detection Using Neural Networks for Second Language Learners
A series of algorithms that aims to recognize underlying relationships in a set of data through a process that mimics how the human brain operates.
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Reinforcement Learning in Social Media Marketing
A supervised learning algorithm, based on layers of weighted sums, suitable for classification.
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Application of Deep Learning for EEG
A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.
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Virtual Try-On With Generative Adversarial Networks: A Taxonomical Survey
A class of machine learning technique vaguely inspired from biological neurons. Mostly synonymous with ‘deep learning’.
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Performance Analysis of GAN Architecture for Effective Facial Expression Synthesis
An artificial network of nodes, used for predictive modelling. It is generally used to tackle classification problems and AI related applications.
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An Analysis and Detection of Misleading Information on Social Media Using Machine Learning Techniques
Various machine learning methods are employed to aid with categorization issues. The neural network is also one of the techniques used for allocation and optimization.
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New Developments in Intracoronary Ultrasound Processing
A modelling technique based on the observed behaviour of biological neurons and used to mimic the performance of a system. It consists of a set of elements (neurons) that start out connected in a random pattern, and, based upon operational feedback, are modelled into the pattern required to generate the optimal results.
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Use of the Neural Network Controller of Sprung Mass to Reduce Vibrations From Road Irregularities
Is a mathematical model, as well as its software or hardware embodiment, built on the principle of the organization and functioning of biological neural networks.
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Estimating Importance From Web Reviews Through Textual Description and Metrics Extraction
A set of algorithms based on human brain usually used to recognize patterns.
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Scientific Workflows for Game Analytics
an architecture of inter-connected, relatively simple, computational nodes (neurons), where the strength (weight) of the connections allows various input vectors to be mapped to outputs in an relatively arbitrary fashion, thus facilitating classification tasks.
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Medication Discovery Using Neural Networks
A neural network is a progression of calculations that perceive essential connections in a data set, a process that imitates the manner in which the human cerebrum works. In this sense, brain networks allude to frameworks of neurons, either natural or fake.
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Applying CI in Biology through PSO
Neural network is a soft computing paradigm inspired by the working of human brain to inculcate intelligence in machines.
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A 2D Positioning Application in PET Using ANNs
A network of many simple processors (“units” or “neurons”) that imitates a biological neural network. The units are connected by unidirectional communication channels, which carry numeric data. Neural networks can be trained to find nonlinear relationships in data, and are used in applications such as robotics, speech recognition, signal processing or medical diagnosis.
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Movement Prediction Oriented Adaptive Location Management
When the work is performed on artificial neural network then it is known as neural network. The knowledge is acquired by the neural network from the environment through the learning process.
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Non-Technological and Technological (SupTech) Innovations in Strengthening the Financial Supervision
A set of interconnected units or nodes which are similar in functioning to the animal neuron with the ability to learn from training patterns. It is modelled on the structure of the human brain and can be used to solve problems in such fields as economics, statistics, and technology.
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Comparing Conventional Methods With Fuzzy Logic for Quantifying Road Congestion: Evidence From Central Kolkata, India
Various machine learning methods are employed to aid with categorization issues. The neural network is also one of the techniques used for allocation and optimization.
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Tuning Drone Data Delivery and Analysis on the Public Cloud
A segregated computer system program that uses example points and processes a set of data based on these points to give specific results.
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Efficient End-to-End Asynchronous Time-Series Modeling With Deep Learning to Predict Customer Attrition
A supervised machine learning algorithm that searches for a function to fit existing data via an iterative training process. Neural Networks are characterized by multiple hidden layers that consist of neurons with activation functions that adjust weights using the backpropagation algorithm and a loss function.
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The Exploration of Autonomous Vehicles
Is inspired by the biological neural networks that constitute animal brains. It consists of a series of algorithms that discover underlying patterns in a dataset through a process that mimics the way the human brain operates.
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Plant Disease Classification Using Deep Learning Techniques
It is a type of machine learning algorithm modeled after the structure and function of the human brain, consisting of interconnected nodes that work together to process input data and produce output predictions.
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Reinforcement Learning for Combinatorial Optimization
A series of algorithms can extract relationships from data through mimicking the operation way of human brain.
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A Big Data Framework for Decision Making in Supply Chain
Neural network is an information processing paradigm that is inspired by the way biological nervous systems, such as brain, process information. It uses a classification mechanism that is modelled after the brain and operates by modifying the input through use of weights to determine what it should output.
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A Novel Fuzzy Logic Classifier for Classification and Quality Measurement of Apple Fruit
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Nonlinear Vibration Control of 3D Irregular Structures Subjected to Seismic Loads
A computational model that is used to predict results depending on a large number of unknown input data. This model becoming popular day by day. Because the neural network can learn from the input data and react according to the demand.
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Particle Swarm Optimization Algorithm as a Tool for Profiling from Predictive Data Mining Models
Mathematical modelinspired on human neural systemwhich has ability to learn from data.
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Neural Networks for Automobile Insurance Pricing
Non-linear predictive models that learn through training and resemble biological neural networks in structure.
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Using Sentiment Analytics to Understand Learner Experiences in Serious Games
A machine learning model that mimics the human brain’s neural network. It contains layers of interconnected nodes (referred to as neurons) to understand and learn from the data.
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Rough Set-Based Neuro-Fuzzy System
A network of many simple processors called units or neurons. A neural network is capable of learning the nonlinear relationships in data.
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