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CVML 2025: International Conference on Computer Vision and Machine Learning

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投稿締切日:
2025-09-19 Extended
通知日:
2025-09-30
開催日:
2025-02-21
開催地:
Chengdu, China
閲覧: 8031   フォロー: 1   参加: 0

論文募集

CVML 2025 (International Conference on Computer Vision and Machine Learning) is an academic conference held in Chengdu, China on 2025-02-21. The paper submission deadline is 2025-09-19 (extended). Acceptance notifications are sent on 2025-09-30.

2025年计算机视觉与机器学习研究国际学术会议(CVML2025），由武汉大学和成都信息工程大学联合举办，将于2025年10月24-26日在四川省成都市举行。截稿日期2025年9月19日，诚邀广大师生投稿参会转发宣传！谢谢！ 在CVML2025会议被录用且完成注册的论文，将由SPIE出版，并提交至EI核心以及Scopus检索。 ------------------------------------ 学术会议云：https://www.allconfs.org/meeting/index.asp?id=36418 --------------------------------------------------------------------------------------- Conference information: 1. Conference Name: 2025 International Conference on Computer Vision and Machine Learning 2. Dates: October 24-26, 2025 3. Organizer: Wuhan University 4. Indexing: EI Compendex, Scopus 5. Format: Hybrid (Virtual & In-person) 6. Website: https://iccvml.com/ --------------------------------------------------------------------------------------- INDEXING Accepted and presented papers will be submitted to El Compendex and Scopus for indexing. 收录检索：EI Compendex，Scopus【多名大咖主讲 | EI稳定检索】 --------------------------------------------------------------------------------------- FULL PAPER SUBMISSION Please refer to the Submission Guidelines for specific information and submission requirements: https://iccvml.com/?submissionguidelines/ 请选择以下投稿方式之一： CMT系统：https://cmt3.research.microsoft.com/CVML2025 电子邮件： iccvml@hotmail.com 注意：所有论文均应以英文撰写，篇幅不得少于4页。 --------------------------------------------------------------------------------------- 会议日期 一轮截稿日期：2025年9月19日 录用通知日期：投稿7个工作日内 会议召开日期：2025年10月24-26日 --------------------------------------------------------------------------------------- Topic Areas This is a non-comprehensive list of topics of interest to CVML 2025. 1. Computer Vision and Imaging: - 3D from multi-view and sensors - 3D from single images - Autonomous driving - Biometrics - Computational imaging - Computer vision theory - Efficient and scalable vision - Explainable computer vision - Humans: Face, body, pose, gesture, movement - Image and video synthesis and generation - Physics-based vision and shape-from-X - Recognition: Categorization, detection, retrieval - Scene analysis and understanding - Segmentation, grouping, and shape analysis - Video: Action and event understanding 2. Machine Leaning Techniques: - Adversarial attack and defense - Deep learning architectures and techniques - Machine learning (other than deep learning) - Optimization methods (other than deep learning) - Transfer/ low-shot/ continual/ long-tail learning - Generative models - Probabilistic methods (Bayesian methods, variational inference, sampling, UQ, etc.) - Reinforcement learning - Representation learning for computer vision, audio, language, and other modalities - Metric learning, kernel learning, and sparse coding - Learning on graphs and other geometries and topologies 3. Ethics, Privacy, and Integrative Techniques: - Transparency, fairness, accountability, privacy, and ethics in vision - Vision, language, and reasoning - Self-& semi-& meta-& unsupervised learning - Robotics --------------------------------------------------------------------------------------- CONTACT Dr. Deng: iccvml@hotmail.com Ms. Li (Wechat): 17722135859
最終更新：Clara Tsai（）

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関連ジャーナル

CCF正式名称インパクトファクター出版社ISSN
cMachine Vision and Applications2.3Springer0932-8092
bMachine Learning2.9Springer0885-6125
bIEEE Transactions on Multimedia9.7IEEE1520-9210
cKnowledge-Based Systems7.2Elsevier0950-7051
bSoftware & Systems Modeling3.2Springer1619-1366
aIEEE Transactions on Computers3.8IEEE0018-9340
cFuture Generation Computer Systems6.1Elsevier0167-739X
cNeurocomputing6.5Elsevier0925-2312
cPattern Recognition Letters3.9Elsevier0167-8655
bPattern Recognition7.6Elsevier0031-3203

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