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HCIML 2027: International Conference on Human-Computer Interaction and Machine Learning

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截稿日期:
2027-03-20 还有 176 天
通知日期:
2027-04-20
会议日期:
2027-06-04
会议地点:
Fushun, China
届数:
浏览: 1145   关注: 0   参加: 0

会伴指数 (CP-I)

40.0 / 100
全站第 5,068 名 / 共 5,687 个会议 · 前 90%

人机交互 第 140 / 154 人工智能与机器学习 第 651 / 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%)
30
社区关注 (10%)
13
资料公开度 (15%)
35

用到的输入: 有据可查的届次：2 · 过去 24 个月打开过本页的研究者：5 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 2026-09-25

征稿

HCIML 2027 (International Conference on Human-Computer Interaction and Machine Learning) is an academic conference held in Fushun, China on 2027-06-04. The paper submission deadline is 2027-03-20. Acceptance notifications are sent on 2027-04-20.

2027 3rd International Conference on Human-Computer Interaction and Machine Learning provides a premier forum for the presentation of new advances and research results in the fields of Human-Computer Interaction and Machine Learning. The conference will bring together leading researchers, scholars and scientists in the domain of interest from around the world. The topics of interest for submission include, but are not limited to: ◕ Track 1: Human-Computer Interaction Multimodal Interaction Natural User Interfaces Affective Computing and Emotional Interaction Brain-Computer Interface and Neural HCI Ubiquitous Computing and Context-Aware Interaction Interactive Data Visualization and Visual Analytics Virtual, Augmented, and Mixed Reality Interaction Human-AI Collaboration and Intelligence Augmentation Interaction Design and UX Evaluation Methods Accessibility and Inclusive Design Social Robotics and Human-Robot Dialogue Interaction Sustainable HCI Mobile and Wearable Interaction Computer-Supported Cooperative Work Privacy, Security, and Ethics in HCI Child-Computer Interaction Embodied and Spatial Interaction ◕ Track 2: Machine Learning Foundations and Algorithms of Large Language Models Generative Models and Creative AI Explainable AI and Trustworthy Machine Learning Robustness and Adversarial Machine Learning Federated Learning and Distributed Machine Learning Self-Supervised and Unsupervised Learning Graph Machine Learning Few-Shot Learning and Transfer Learning Reinforcement Learning and Intelligent Decision-Making Multimodal Machine Learning Neural-Symbolic Integration AI for Science Online Learning and Continual Learning Machine Learning Systems and Hardware Acceleration Bio-Inspired Learning Algorithms Security and Privacy in Machine Learning Efficiency Optimization of Machine Learning Models
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