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Improved YOLOv3 Integrating SENet and Optimized GIoU Loss for Occluded Pedestrian Detection
Occluded pedestrian detection faces huge challenges. False positives and false negatives in crowd occlusion scenes will reduce the accuracy of occluded pedestrian detection. To overcome this problem, we proposed an improved you-only-look-once version 3 (YOLOv3) based on squeeze-and-excitation networ...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675795/ https://www.ncbi.nlm.nih.gov/pubmed/38005475 http://dx.doi.org/10.3390/s23229089 |