Ren, Shenghao (2025) Optimizing Human Pose Estimation Using a Simplified UNet Architecture: An Experimental Analysis on Depth and Width Parameters. In: Proceedings of the 2nd International Conference on Machine Learning and Automation, CONF-MLA 2024, November 21, 2024, Adana, Turkey.
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Abstract
Human pose estimation (HPE) is a significant problem in the field of computer vision, with wide applications in action recognition, intelligent surveillance, and other areas. With the development of deep learning, the accuracy of pose estimation has significantly improved. However, high-precision po
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 18:27 |
| Last Modified: | 16 Apr 2026 21:38 |
| URI: | http://eprints.eai.eu/id/eprint/52544 |
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