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ICONS 2026: ACM International Conference on Neuromorphic Systems

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截稿日期:
2026-04-08 Extended
通知日期:
2026-06-05
会议日期:
2026-08-04
会议地点:
Chicago, Illinois, USA
浏览: 1516   关注: 0   参加: 0

会伴指数 (CP-I)

43.8 / 100
全站第 3,382 名 / 共 5,693 个会议 · 前 60%
证据有限：这个会议不在 CCF / ICORE / QUALIS 任何一份榜单里，也没有录用率数据，因此分数的大部分回落到了中性基准。
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%) 无数据 —— 按中性基准 50 分计入 —
社区关注 (10%)
10
资料公开度 (15%)
35

用到的输入: 过去 24 个月打开过本页的研究者：3 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 25% —— 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 2026-10-04

征稿

ICONS 2026 (ACM International Conference on Neuromorphic Systems) is an academic conference held in Chicago, Illinois, USA on 2026-08-04. The paper submission deadline is 2026-04-08 (extended). Acceptance notifications are sent on 2026-06-05.

Neuromorphic computing has the potential to transform the way we use computers through new materials, new brain-inspired chips, greater understanding of neuroscience, and breakthroughs in low-energy/edge AI. Neuromorphic computing systems, we believe, will lead to more powerful and efficient computing paradigms. The goal of this conference is to bring together leading researchers in neuromorphic computing to present new research, develop new collaborations, and provide a forum to publish work in this area. Focus Areas We welcome submissions in the areas of neuromorphic computing, neural-inspired computing, and neuroscience-inspired AI. Below is a list of focus areas of particular interest. Systems, architectures, circuits, devices, and materials Neuromorphic circuits or sensors Non-von Neumann computing architectures and models Emerging devices and hardware implementations Event or spike-based systems Novel brain-inspired system architectures Algorithms for training, configuring, or programming Supervised, unsupervised and self-supervised learning methods Biologically-inspired algorithms Adaptations to existing algorithms for use on or with neuromorphic systems Continual learning systems Applications and use-cases Energy Efficient Edge-AI Applications Biomedical Applications Applications demonstrating a neuromorphic or neural-inspired advantage Benchmark tasks for neuromorphic computing Neuromorphic datasets Domain-specific adaptation Software and interfaces for neuromorphic systems Efficient simulation techniques for large-scale networks Compilers, programming frameworks and related methodology Visualization and insight tools Note: This is a non-exhaustive list and submissions outside the scope of these areas will also be considered.
由 Dou Sun 最后更新于

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