MCA-YOLOV5-Light: A Faster, Stronger and Lighter Algorithm for Helmet-Wearing Detection

MCA-YOLOV5-Light: A Faster, Stronger and Lighter Algorithm for Helmet-Wearing Detection

It is an essential measure for workers to wear safety helmets when entering the construction site to prevent head injuries caused by object collision and falling. This paper proposes a lightweight algorithm for helmet-wearing detection based on YOLOV5, which is faster and more robust for helmet dete...

Бүрэн тодорхойлолт

Номзүйн дэлгэрэнгүй
Үндсэн зохиолчид:	Cheng Sun, Shiwen Zhang, Peiqi Qu, Xingjin Wu, Peng Feng, Zhanya Tao, Jin Zhang, Ying Wang
Формат:	Өгүүллэг
Хэл сонгох:	English
Хэвлэсэн:	MDPI AG 2022-09-01
Цуврал:	Applied Sciences
Нөхцлүүд:	helmet-wearing detection YOLOv5 attention mechanism model pruning
Онлайн хандалт:	https://www.mdpi.com/2076-3417/12/19/9697

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