id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
brj-24141	Li, Rui; Zhong, Shilu; Yang, Xuemei	Wood Panel Defect Detection Based on Improved YOLOv8n	2025	18	.pdf	application/pdf	6067	316	47	To address these challenges, this paper conducts a thorough investigation of the YOLOv8n model and proposes several enhancements to bolster its performance in detecting wood panel surface, thereby better aligning with the practical demands of wood defect detection. Fig. In the field of wood panel defect detection, some defects are often obscured by the features of large targets due to their small size and inconspicuous features, leading to poor performance of target detection models such as YOLOv8 in recognizing small targets.	cache/brj-24141.pdf	txt/brj-24141.txt