会议信息

NCTA 2026: International Conference on Neural Computation Theory and Applications

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截稿日期:
2026-07-03 还有 4 天 Extended
通知日期:
2026-07-17
会议日期:
2026-10-28
会议地点:
Angers, France
届数:
18
浏览: 16271   关注: 0   参加: 0

征稿

NCTA 2026 (International Conference on Neural Computation Theory and Applications) is an academic conference held in Angers, France on 2026-10-28. The paper submission deadline is 2026-07-03 (extended). Acceptance notifications are sent on 2026-07-17.

SCOPE 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. CONFERENCE TOPICS Adaptive Architectures and Mechanisms Applications: Image Processing and Artificial Vision, Pattern Recognition, Decision Making, Industrial and Real World Applications, Financial Applications, Neural Prostheses and Medical Applications, Neural Based Data Mining and Complex Information Process Complex Artificial Neural Network Based Systems and Dynamics Computational Neuroscience Convolutional Neural Networks Deep Learning Higher Level Artificial Neural Network Based Intelligent Systems Learning Paradigms and Algorithms Neural Approaches and Neural Architectures Recurrent Neural Networks Reinforcement Learning Bio-inspired models and solutions Stability and Instability in Artificial Neural Networks Stochastic Learning and Statistical Algorithms Support Vector Machines and Kernel Methods Neural based Implementation, Applications and Solutions
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相关期刊

CCF全称影响因子出版商ISSN
BNeural Computation2.1MIT Press0899-7667
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