id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-29385	Ruan, Xingyan; Luo, Li; Yu, Xiangyang; Cai, Yefan; Hong, Weibin	Rapid Textile Fibers Classification Technology Based on Near-Infrared Spectroscopy and Machine Learning	2025	8	.pdf	application/pdf	4168	197	45	Although these issues increase the difficulty of sample classification, properly handling spectral drift and fluctuations can enhance the robustness of the classification model, reduce noise interference, and uncover potential information, thereby improving the scientific validity and accuracy of the classification. When the class distribution of sample data is imbalanced, accuracy may not fully assess the model's performance.	cache/fcis-29385.pdf	txt/fcis-29385.txt