id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-31913	Zhang , Yuan; Ding, Xuewen; Jiang, Xiaokai; Wang, Shaosai	Research on Wood Defect Detection Algorithms Based on Improved Neural 	2025	8	.pdf	application/pdf	5309	266	35	Despite significant advancements in deep learning technologies for wood defect detection, existing algorithms still face limitations due to factors such as complex texture backgrounds, diversity in defect types, and some defects being small in size. Therefore, this study addresses key issues in wood defect detection by proposing a more targeted deep learning object detection algorithm aimed at improving adaptability and reliability in complex scenarios while providing more effective technical support for quality control in the wood industry.	cache/fcis-31913.pdf	txt/fcis-31913.txt