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PRML 2026: International Conference on Pattern Recognition and Machine Learning

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PRML
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截稿日期:
2026-05-15 Extended
通知日期:
2026-05-30
会议日期:
2026-07-10
会议地点:
Urumqi, China
届数:
7
浏览: 19241   关注: 8   参加: 0

会伴指数 (CP-I)

48.1 / 100
全站第 1,931 名 / 共 5,650 个会议 · 前 35%

计算机视觉与模式识别 第 87 / 241 人工智能与机器学习 第 197 / 734

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%)
56
社区关注 (10%)
42
资料公开度 (15%)
35

用到的输入: 有据可查的届次：7 · 在会伴关注它的研究者：8 人 · 过去 24 个月打开过本页的研究者：14 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 2026-09-04

征稿

PRML 2026 (International Conference on Pattern Recognition and Machine Learning) is an academic conference held in Urumqi, China on 2026-07-10. The paper submission deadline is 2026-05-15 (extended). Acceptance notifications are sent on 2026-05-30.

PRML is an annual conference which aims to present the latest research and results of scholars and experts related to Pattern Recognition and Machine Learning. Topics of interest for submission include, but are not limited to: Track 1: Computer Vision and Recognition ◇ Image and Video Classification ◇ Object Detection and Tracking ◇ Semantic Segmentation ◇ Content-based Image Retrieval ◇ Facial Recognition ◇ 3D Reconstructions ◇ Action Recognition Track 2: Deep Learning and Optimization ◇ Neural Generative Models, Autoencoders, GANs ◇ Optimization and Learning Methods ◇ Representation Learning and Deep Learning ◇ Scene Analysis and Understanding ◇ Transfer Learning, Low-Shot, Semi- and Unsupervised Learning ◇ Motion and Tracking Track 3: Artificial Intelligence (AI) in Biomedical Applications ◇ AI in Biomedical Signal and Image Processing ◇ Bioinformatics for Healthcare Engineering ◇ Explainable AI, Fairness, Accountability, Privacy, Transparency and Ethics in Vision ◇ Biomedical Image Retrieval, Segmentation, Grouping and Shape using AI ◇ Applying Machine Learning-empowered Sensing to Biomedical Scenarios ◇ Distributed Computing for Big Data in Smart Healthcare using AI ◇ AI-enabled Remote Patient Monitoring using Big Data Track 4: Vision Applications and Systems ◇ Segmentation, Grouping, and Shape ◇ Vision + Language, Vision + Other Modalities ◇ Video Analysis and Understanding ◇ Vision Applications and Systems ◇ Vision for Robotics and Autonomous Vehicles ◇ Visual Reasoning and Logical Representation Track 5: Artificial Intelligence (AI) for Data Analytics ◇ Data Clustering, Classification, and Visualisation ◇ Explainable AI and Knowledge Discovery from Databases ◇ Fintech, Business Intelligence, Marketing Analytics, Risk Analytics and Decision Support ◇ Medical Diagnosis and Prognosis, Biomedical and Healthcare Analytics ◇ Predictive Maintenance, Condition Monitoring, Manufacturing Analytics ◇ Data Mining in Education, Transportation, Telecommunication, Agriculture, Energy, etc.
由 Dunn Carl 最后更新于

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