id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-5050	Li, Xiuyu ; Tanjong, Shirley J. 	Bearing fault diagnosis in high noise environment using multi-scale processing, channel-attention and feature-enhanced convolutional neural network model	2025	15	.pdf	application/pdf	6471	354	50	The corresponding output is the fault type 𝑌𝑡, for model fault diagnosis. Deep learning has deep structures and effective nonlinear feature-extraction capabilities, enabling it to extract fault features directly from raw data and achieve end-to-end fault diagnosis, avoiding the tedious feature-extraction and classification steps of traditional methods.	cache/easat-5050.pdf	txt/easat-5050.txt