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A Recursive Constrained Framework for Unsupervised Video Action Clustering

  • Published:2020-01 Issue:1 Volume:16 Page:555-565
  • ISSN:1551-3203
  • Container-title:IEEE Transactions on Industrial Informatics
  • language:
  • Short-container-title:IEEE Trans. Ind. Inf.

Author:

Peng BoORCID,Lei JianjunORCID,Fu HuazhuORCID,Shao LingORCID,Huang QingmingORCID

Funder

National Key Research and Development Program of China Stem Cell and Translational Research

National Natural Science Foundation of China

Natural Science Foundation of Tianjin City

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Flexible multi-objective particle swarm optimization clustering with game theory to address human activity discovery fully unsupervised;Image and Vision Computing;2024-05

2. Superheat Degree Category Refinement of Aluminum Electrolysis Cell Using Flame Hole Video Apparent Spatio-Temporal Feature Clustering Network;2023 China Automation Congress (CAC);2023-11-17

3. Content-Based Video Clustering Using Hybrid Multi -View Spatio- Temporal Feature Learning;2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE);2023-11-17

4. A clustering algorithm of network short video based on text and video model;2023 4th International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE);2023-08-25

5. A Novel Skeleton-Based Human Activity Discovery Using Particle Swarm Optimization With Gaussian Mutation;IEEE Transactions on Human-Machine Systems;2023-06
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