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What is Convolutional Neural Networks (CNN)

Chapter 75
Encyclopedia of Criminal Activities and the Deep Web
A special type of neural networks used popularly to analyze photography and imagery.
Published in Chapter:
Hybrid Artificially Intelligent Multi-Layer Blockchain and Bitcoin Cryptology (AI-MLBBC): Anti-Crime-Theft Smart Wall Defense
Murad Al Shibli (Abu Dhabi Polytechnic, UAE)
Copyright: © 2020 |Pages: 23
DOI: 10.4018/978-1-5225-9715-5.ch075
Abstract
This article presents an integrated secured framework of blockchain and bitcoin cryptology with the artificial intelligence of neural networks and machine learning. Recently blockchain has received special attention and been used as a new platform for digital information and to store encrypted data and process secure digital transactions. Furthermore, data on blockchain and bitcoin platforms are assumed to be highly encrypted and secured. Although blockchain and bitcoin databases are encrypted using private keys, many cryptocurrency bitcoin wallets have been reported hacked, which has resulted in losing millions of dollars. The artificial intelligent neural networks (AINN) algorithms possess the capability features of processing and operating encrypted data and will lead to minimal risk as a part of the blockchain to protect personal data and information as third wall defense against hacking. Simulation results and analysis demonstrates the effectiveness of this technique for protecting personal data and financial information.
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Chapter 9
Design of an IoT-Based Quantity Controlled Pesticide Sprayer Using Plant Identification
It is a class of deep learning technology mainly used for accurate classification of images.
Published in Chapter: Design of an IoT-Based Quantity Controlled Pesticide Sprayer Using Plant Identification; From: IoT Protocols and Applications for Improving Industry, Environment, and Society
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Chapter 4
Next Generation of Intelligent Cities: Case Studies From Europe
They are a class of deep neural networks that are generally used to analyze image data. They use convolution instead of simple matrix multiplication in a few layers of the network. They have shared weights architecture and have translation invariant characteristics.
Published in Chapter: Next Generation of Intelligent Cities: Case Studies From Europe; From: Developing and Monitoring Smart Environments for Intelligent Cities
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Chapter 10
Deep Learning-Based Mobile Application for Plant Disease Diagnosis: A Proof of Concept With a Case Study on Tomato Plant
It is a subtype of ANNs with a collection of deep FFNNs utilized mainly for image analysis and classification.
Published in Chapter: Deep Learning-Based Mobile Application for Plant Disease Diagnosis: A Proof of Concept With a Case Study on Tomato Plant; From: Applications of Image Processing and Soft Computing Systems in Agriculture
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Chapter 10
Analysis of Ethical Development for Public Policies in the Acquisition of AI-Based Systems
It is a type of deep learning model commonly used for images-related tasks. It uses the mathematical operation of convolution to extract features from images.
Published in Chapter: Analysis of Ethical Development for Public Policies in the Acquisition of AI-Based Systems; From: Exploring Ethical Problems in Today’s Technological World
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Chapter 7
Classification and Assessment of Visual Content of Medicinal Plants Using CNN
It is deep learning model uniquely suited for tasks like medicinal plant classification due to their ability to learn hierarchical features from images. The versatility and accuracy of CNNs make them indispensable in a wide range of applications beyond plant classification.
Published in Chapter: Classification and Assessment of Visual Content of Medicinal Plants Using CNN; From: Handbook of Research on Innovative Approaches to Information Technology in Library and Information Science
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Chapter 2
Survey of Applications of Neural Networks and Machine Learning to COVID-19 Predictions
In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery.
Published in Chapter: Survey of Applications of Neural Networks and Machine Learning to COVID-19 Predictions; From: Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning
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