Human Action Recognition Using Multi-Stream Fusion and Hybrid Deep Neural Networks-Reference-Cited by-同舟云学术

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Human Action Recognition Using Multi-Stream Fusion and Hybrid Deep Neural Networks

Published:2023-10-01 Issue: Volume:27 Page:4852-4858
ISSN:
Container-title:2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
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Author:

Chopra Saurabh¹,Zhang Li¹,Jiang Ming²

Affiliation:

1. University of London,Department of Computer Science Royal Holloway,Surrey,United Kingdom

2. Faculty of Technology,Department of Computer Science,Sunderland,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391856/10393862/10393912.pdf?arnumber=10393912

Reference25 articles.

1. UCF101: A dataset of 101 human actions classes from videos in the wild;Soomro;arXiv preprint,2012

2. Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization

3. Enhanced bare-bones particle swarm optimization based evolving deep neural networks

4. Learning Spatio-Temporal Representation With Local and Global Diffusion

5. A Closer Look at Spatiotemporal Convolutions for Action Recognition

Cited by 1 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. Smarter Aging: Developing a Foundational Elderly Activity Monitoring System With AI and GUI Interface;IEEE Access;2024

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