会议信息

AIAHPC 2025: International Conference on Artificial Intelligence, Automation and High Performance Computing

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AIAHPC
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截稿日期:
2025-09-12
通知日期:
2025-09-13
会议日期:
2025-09-19
会议地点:
Hefei, China
届数:
5
浏览: 16708   关注: 6   参加: 1

会伴指数 (CP-I)

45.5 / 100
全站第 2,750 名 / 共 5,693 个会议 · 前 49%

机器人与控制 第 169 / 470 系统与体系结构 第 222 / 341 人工智能与机器学习 第 297 / 742

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%)
48
社区关注 (10%)
31
资料公开度 (15%)
35

用到的输入: 有据可查的届次：5 · 在会伴关注它的研究者：6 人 · 过去 24 个月打开过本页的研究者：4 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 2026-10-05

征稿

AIAHPC 2025 (International Conference on Artificial Intelligence, Automation and High Performance Computing) is an academic conference held in Hefei, China on 2025-09-19. The paper submission deadline is 2025-09-12. Acceptance notifications are sent on 2025-09-13.

The topics of interest for submission include, but are not limited to: High-performance computing and artificial intelligence technology · Scalable architectures for deep learning · Parallel algorithms for training neural networks · GPU and FPGA-based acceleration of deep learning · HPC in large-scale image and video processing · Simulation and modeling of autonomous systems using HPC · HPC in robotics and unmanned aerial vehicles (UAVs) · HPC for big data analytics and visualization · Scalable machine learning algorithms and frameworks · Distributed computing for AI applications · High-performance data analytics for industrial IoT AI and high-performance computing in automation and manufacturing · Integration of AI and HPC in smart manufacturing · AI models for optimization of production processes · HPC applications in predictive maintenance · AI-driven optimization of HPC resources · Safety and security aspects of HPC in automation · Intelligent Robotics and Autonomous Systems Applications of high-performance computing to new computing technologies and systems · Supercomputing and Quantum Computing · Energy-efficient high-performance computing in AI · Federated Learning and Distributed AI · Distributed Computing and Cloud Computing · Edge Computing and Fog Computing
由 Dou Sun 最后更新于

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