1.

Record Nr.

UNINA9910729895703321

Autore

Iliadis Lazaros

Titolo

Engineering Applications of Neural Networks : 24th International Conference, EAAAI/EANN 2023, León, Spain, June 14–17, 2023, Proceedings / / edited by Lazaros Iliadis, Ilias Maglogiannis, Serafin Alonso, Chrisina Jayne, Elias Pimenidis

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023

ISBN

3-031-34204-6

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (636 pages)

Collana

Communications in Computer and Information Science, , 1865-0937 ; ; 1826

Altri autori (Persone)

MaglogiannisIlias

Alonso NavarroSerafín

JayneChrisina

PimenidisElias

Disciplina

006.32

Soggetti

Artificial intelligence

Computer engineering

Computer networks

Software engineering

Social sciences - Data processing

Education - Data processing

Artificial Intelligence

Computer Engineering and Networks

Software Engineering

Computer Application in Social and Behavioral Sciences

Computers and Education

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Artificial Intelligence - Computational Methods - Ethology -- Classification - Filtering - Genetic Algorithms -- Complex Dynamic Networks' Optimization/ Graph Neural Networks -- Convolutional Neural Networks / Spiking Neural Networks -- Deep Learning Modeling -- Deep/Machine Learning in Engineering -- LEARNING (Reinforcemet - Federated - Adversarial - Transfer) -- Natural Language -



Recommendation Systems.

Sommario/riassunto

This book constitutes the refereed proceedings of the 24th International Conference on Engineering Applications of Neural Networks, EANN 2023, held in León, Spain, in June 2023. The 41 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 125 submissions. The papers are organized in topical sections on artificial intelligence - computational methods - ethology; classification - filtering - genetic algorithms; complex dynamic networks' optimization/ graph neural networks; convolutional neural networks/spiking neural networks; deep learning modeling; deep/machine learning in engineering; LEARNING (reinforcemet - federated - adversarial - transfer); natural language - recommendation systems.