
Proceedings of the 22nd Engineering Applications of Neural Networks Conference
EANN 2021
Springer (Publisher)
Published on 1. July 2021
Book
Paperback/Softback
XLIII, 521 pages
978-3-030-80567-8 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2021
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
160 farbige Abbildungen, 29 s/w Abbildungen
XLIII, 521 p. 189 illus., 160 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 31 mm
Weight
850 gr
ISBN-13
978-3-030-80567-8 (9783030805678)
DOI
10.1007/978-3-030-80568-5
Schweitzer Classification
Other editions
Additional editions

Lazaros Iliadis | John MacIntyre | Chrisina Jayne
Proceedings of the 22nd Engineering Applications of Neural Networks Conference
EANN 2021
E-Book
06/2021
Springer
€309.23
Available for download
Content
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.