Proceedings of the 22nd Engineering Applications of Neural Networks Conference

EANN 2021
Herausgegeben:Iliadis, Lazaros; Macintyre, John; Jayne, Chrisina; Pimenidis, Elias

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Proceedings of the International Neural Networks Society 3
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-80567-8
• 1st ed. 2021
• Seitenzahl: 568
• Erscheinungstermin: 1. Juli 2021
• Englisch
• Abmessung: 235mm x 155mm x 31mm
• Gewicht: 850g
• ISBN-13: 9783030805678
• ISBN-10: 3030805670
• Artikelnr.: 62006496

Inhaltsangabe

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.