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Proceedings of the 22nd Engineering ...
~
(1998 :)
Proceedings of the 22nd Engineering Applications of Neural Networks ConferenceEANN 2021 /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Proceedings of the 22nd Engineering Applications of Neural Networks Conferenceedited by Lazaros Iliadis ... [et al.].
Reminder of title:
EANN 2021 /
remainder title:
EANN 2021
other author:
Iliadis, Lazaros.
corporate name:
Published:
Cham :Springer International Publishing :2021.
Description:
xliii, 521 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
Subject:
Neural networks (Computer science)
Online resource:
https://doi.org/10.1007/978-3-030-80568-5
ISBN:
9783030805685$q(electronic bk.)
Proceedings of the 22nd Engineering Applications of Neural Networks ConferenceEANN 2021 /
Proceedings of the 22nd Engineering Applications of Neural Networks Conference
EANN 2021 /[electronic resource] :EANN 2021edited by Lazaros Iliadis ... [et al.]. - Cham :Springer International Publishing :2021. - xliii, 521 p. :ill., digital ;24 cm. - Proceedings of the international neural networks society,v.32661-8141 ;. - Proceedings of the international neural networks society ;v.1..
Automatic Facial Expression Neutralisation Using Generative Adversarial Network -- Creating Ensembles of Generative Adversarial Network Discriminators for One-class Classification -- A Hybrid Deep Learning Ensemble for Cyber Intrusion Detection -- Anomaly Detection by Robust Feature Reconstruction -- Deep Learning of Brain Asymmetry Images and Transfer Learning for Early Diagnosis of Dementia -- Deep learning topology-preserving EEG-based images for autism detection in infants -- Improving the Diagnosis of Breast Cancer by Combining Visual and Semantic Feature Descriptors -- Liver cancer trait detection and classification through Machine Learning on smart mobile devices.
This book contains the proceedings of the 22nd EANN "Engineering Applications of Neural Networks" 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing on the following algorithms-approaches: Augmented ML, autoencoders, adversarial neural networks, blockchain-adaptive methods, convolutional neural networks, deep learning, ensemble methods, learning-federated learning, neural networks, recurrent - long short-term memory. The application domains are related to: Anomaly detection, bio-medical AI, cyber-security, data fusion, e-learning, emotion recognition, environment, hyperspectral imaging, fraud detection, image analysis, inverse kinematics, machine vision, natural language, recommendation systems, robotics, sentiment analysis, simulation, stock market prediction.
ISBN: 9783030805685$q(electronic bk.)
Standard No.: 10.1007/978-3-030-80568-5doiSubjects--Topical Terms:
181982
Neural networks (Computer science)
LC Class. No.: QA76.87 / .E36 2021
Dewey Class. No.: 006.32
Proceedings of the 22nd Engineering Applications of Neural Networks ConferenceEANN 2021 /
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Automatic Facial Expression Neutralisation Using Generative Adversarial Network -- Creating Ensembles of Generative Adversarial Network Discriminators for One-class Classification -- A Hybrid Deep Learning Ensemble for Cyber Intrusion Detection -- Anomaly Detection by Robust Feature Reconstruction -- Deep Learning of Brain Asymmetry Images and Transfer Learning for Early Diagnosis of Dementia -- Deep learning topology-preserving EEG-based images for autism detection in infants -- Improving the Diagnosis of Breast Cancer by Combining Visual and Semantic Feature Descriptors -- Liver cancer trait detection and classification through Machine Learning on smart mobile devices.
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This book contains the proceedings of the 22nd EANN "Engineering Applications of Neural Networks" 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing on the following algorithms-approaches: Augmented ML, autoencoders, adversarial neural networks, blockchain-adaptive methods, convolutional neural networks, deep learning, ensemble methods, learning-federated learning, neural networks, recurrent - long short-term memory. The application domains are related to: Anomaly detection, bio-medical AI, cyber-security, data fusion, e-learning, emotion recognition, environment, hyperspectral imaging, fraud detection, image analysis, inverse kinematics, machine vision, natural language, recommendation systems, robotics, sentiment analysis, simulation, stock market prediction.
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Intelligent Technologies and Robotics (SpringerNature-42732)
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EB QA76.87 .E12 2021 2021
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https://doi.org/10.1007/978-3-030-80568-5
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