1.

Record Nr.

UNINA9910578684303321

Titolo

Engineering Applications of Neural Networks : 23rd International Conference, EAAAI/EANN 2022, Chersonissos, Crete, Greece, June 17–20, 2022, Proceedings / / edited by Lazaros Iliadis, Chrisina Jayne, Anastasios Tefas, Elias Pimenidis

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022

ISBN

3-031-08223-0

Edizione

[1st ed. 2022.]

Descrizione fisica

1 online resource (544 pages)

Collana

Communications in Computer and Information Science, , 1865-0937 ; ; 1600

Disciplina

006.32

Soggetti

Artificial intelligence

Computer engineering

Computer networks

Social sciences - Data processing

Education - Data processing

Software engineering

Artificial Intelligence

Computer Engineering and Networks

Computer Application in Social and Behavioral Sciences

Computers and Education

Software Engineering

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Bio inspired Modeling / Novel Neural Architectures -- Classification / Clustering - Machine Learning -- Convolutional / Deep Learning -- Datamining / Learning / Autoencoders -- Deep Learning / Blockchain -- Machine Learning for Medical Images / Genome Classification -- Reinforcement /Adversarial / Echo State Neural Networks -- Robotics / Autonomous Vehicles, Photonic Neural Networks -- Text Classification / Natural Language.

Sommario/riassunto

This book constitutes the refereed proceedings of the 23rd International Conference on Engineering Applications of Neural



Networks, EANN 2022, held in Chersonisos, Crete, Greece, in June 2022. The 37 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on Bio inspired Modeling / Novel Neural Architectures; Classification / Clustering; Machine Learning; Convolutional / Deep Learning; Datamining / Learning / Autoencoders; Deep Learning / Blockchain; Machine Learning for Medical Images / Genome Classification; Reinforcement /Adversarial / Echo State Neural Networks; Robotics / Autonomous Vehicles, Photonic Neural Networks; Text Classification / Natural Language.