id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-7168	Lian, Xin; Wang, Dewen	Insulator defect detection algorithm based on improved YOLOv5	2023	4	.pdf	application/pdf	3347	195	52	Experimental results show that this method can improve the identification accuracy of insulator defect detection in transmission lines. Moreover, insulator defect detection has become the main trend of deep learning in power inspection research, which has advantages over traditional detection methods in terms of detection accuracy, speed and generalization ability of model application.	cache/fcis-7168.pdf	txt/fcis-7168.txt