NCTA is part of IJCCI, the 16th International Joint Conference on Computational Intelligence. Registration to NCTA allows free access to all other IJCCI conferences.
IJCCI 2024 will be held in conjunction with ICINCO 2024, icSPORTS 2024, CHIRA 2024, IN4PL 2024, CoopIS 2024 and EXPLAINS 2024.
Registration to IJCCI allows free access to the ICINCO, icSPORTS, CHIRA, IN4PL, CoopIS and EXPLAINS conferences (as a non-speaker).
Although the conference is back to the normal mode (i.e., in-person) speakers are allowed to present remotely if unable to travel to the venue (hybrid support).
Neural computation and artificial neural networks, especially in relation to deep learning, have seen an explosion of interest over the recent decades, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicine, engineering, geology and physics, in problems of complex dynamics and complex behavior prediction, classification or control. Several architectures, learning strategies and algorithms have been introduced in this highly dynamic field in the last couple of decades. Nowadays, having reached notable scientific and applicative maturity, neural computation and related techniques are considered as major basis toward the completion of intelligent artificial systems. This conference intends to be a major forum for scientists, engineers and practitioners interested in the study, analysis, design, modeling and implementation of neural computing systems, both theoretically and in a broad range of application fields.
Joaquim Filipe, Polytechnic Institute of Setubal / INSTICC, Portugal
Kurosh Madani, University of Paris-EST Créteil (UPEC), France
João Gama, University of Porto, PortugalTome Eftimov, Jožef Stefan Institute, SloveniaGabriela Ochoa, University of Stirling, United Kingdom
Publications:
A short list of presented papers will be selected
so that revised and extended versions of these
papers will be published by Springer in a
SCI Series book
Proceedings will be submitted for evaluation for indexing by: