An Improved Transformer-Based Model for Urban Pedestrian Detection
Abstract Pedestrian detection is a crucial task in computer vision, applicable in object tracking, video surveillance, and autonomous driving. Recent years have witnessed substantial advancements in pedestrian detection due to the fast evolution of deep learning in object detection. Nonetheless, obs...
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| Main Authors: | Tianyong Wu, Xiang Li, Qiuxuan Dong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-03-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-025-00791-x |
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