id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
brj-22874	Tian, Siqing; Li, Xiao; Fang, Xiaolin; Qi, Xiaozhong; Li, Jichao	Surface Defect Detection Method of Wooden Spoon Based on Improved YOLOv5 Algorithm 	2023	18	.pdf	application/pdf	6741	381	59	The SPPnet module is used as a variable and added to different positions of the backbone network to increase the receptive field to extract important defect features and improve the accuracy of wood spoon defect detection. The experimental results show: The YOLOv5-TSPP algorithm has better detection performance and the mAP of defect detection reaches 80.3%, which is 9.2% higher than that of the YOLOv5 algorithm.	cache/brj-22874.pdf	txt/brj-22874.txt