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ICAIM 2027: International Conference on Artificial Intelligence & Materials

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截稿日期:
2027-01-10 还有 115 天
通知日期:
2027-02-20
会议日期:
2027-03-12
会议地点:
Changsha, China
届数:
浏览: 5860   关注: 0   参加: 0

会伴指数 (CP-I)

44.3 / 100
全站第 3,094 名 / 共 5,682 个会议 · 前 55%

材料、机械与制造 第 83 / 260 人工智能与机器学习 第 362 / 739

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%)
37
社区关注 (10%)
10
资料公开度 (15%)
55

用到的输入: 有据可查的届次：3 · 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) · 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 2026-09-17

征稿

ICAIM 2027 (International Conference on Artificial Intelligence & Materials) is an academic conference held in Changsha, China on 2027-03-12. The paper submission deadline is 2027-01-10. Acceptance notifications are sent on 2027-02-20.

The International Conference on Artificial Intelligence and Materials (ICAIM) committed to the deep integration and common enhancement in materials science, artificial intelligence (AI) technology. Topics of interest for submission include: Artificial Intelligence Adaptive Systems Fuzzy Logic Data Mining Machine Learning Deep Learning Inductive Learning Intelligent and Knowledge Based System Natural Language Processing Signal Processing Computer Vision Virtual Reality Augmented Reality Hybrid and Nonlinear system Intelligent Control Bioinformatics Pattern Recognition Knowledge Discovery Intelligent Data Analysis Neural Networks Genetic Algorithms Medical Diagnostics S upport Vector Machines Machine Vision Intelligent Systems and Language Materials Nanomedical materials Regenerative biomaterials Materials with engineered interfaces Self-assembled materials Materials with selective mechanical and functional properties Materials for soft and hard tissue reconstruction and regeneration 3D/4D printing for bioactive materials Hydrogen Energy Materials Biomass Energy Materials Geothermal Energy Materials Nuclear Materials Environmental Friendly Materials Electrolyte Materials Photovoltaic Materials Semiconductors and Semiconductor Devices Superconductors and Superconducting Materials Advanced manufacturing materials Catalyst Materials Light Emitting Materials Acoustic Materials Structured Materials AI & Materials Biomaterials modeling, design, and AI applications AI for materials science Digital twin technology with AI for materials industry Modelling techniques for manufacturing processes and systems boosted with AI Materials theory assisted by AI technology Novel AI lgorithms that have potential applications to materials AI in Materials Informatics and Data-Driven Research AI for Sustainable Materials Development AI for Predicting Material Failure and Durability AI-Enhanced Materials for Energy Applications AI in Advanced Manufacturing and Materials Processing Machine Learning for Computational Materials Science AI-Driven Materials Discovery and Design
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