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NCTA 2026: International Conference on Neural Computation Theory and Applications

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截稿日期:
2026-07-03 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: 17197   关注: 0   参加: 0

会伴指数 (CP-I)

50.1 / 100
全站第 1,581 名 / 共 5,687 个会议 · 前 28%

人工智能与机器学习 第 155 / 741

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
79
社区关注 (10%)
15
资料公开度 (15%)
35

用到的输入: 有据可查的届次：18 · 过去 24 个月打开过本页的研究者：6 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-28

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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