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This study presents an improved YOLOv5 algorithm integrated with the SE attention mechanism to enhance person and vehicle detection and counting in urban environments. The proposed method addresses challenges such as object occlusion and background interference, achieving a 6.63% performance improvement over the baseline YOLOv5 model. Experimental results on the BDD100K dataset demonstrate the algorithm
- Author
- ijaia
- Language
- EN