Based on the YOLOv7 model, the YOLOv7-globel attention mechanism (YOLO-GAM) model was proposed to enhance the model's focus on critical regions. Additionally, a multi-scale training scheme was introduced to improve the model's ability to detect small targets, and a two-stage enhanced detection algorithm was designed, which effectively mitigated the degradation of detection performance caused by occlusion, overlapping, and small targets. With an input image resolution of $640\times 640$, the scheme's detection speed could meet the real-time requirements of the actual production environment and outperform the related algorithms in terms of performance.
ZHU Shuo
,
WANG Yongfang
,
LI Zixuan
,
CHEN Wei
. Real-time reflective vest detection in operational environments based on YOLO[J]. Journal of Shanghai University, 2025
, 31(4)
: 691
-703
.
DOI: 10.12066/j.issn.1007-2861.2686
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