Improving unsupervised pedestrian re‐identification with enhanced feature representation and robust clustering
Abstract Pedestrian re‐identification (re‐ID) is an important research direction in computer vision, with extensive applications in pattern recognition and monitoring systems. Due to uneven data distribution, and the need to solve clustering standards and similarity evaluation problems, the performa...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-12-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cvi2.12309 |
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