id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-3173	Zhang, Wen; Sun, Shibao; Yang, Huanjing	Research on aluminum defect classification algorithm based on deep learning with attention mechanism	2022	5	.pdf	application/pdf	3548	201	47	Convolutional neural networks (CNNs) extract features differently from manual extraction, but learn features and extract them from the data itself, with better results and greater robustness. [12] implemented wood defect recognition classification by convolutional neural network and this method does not require complex pre-processing of images and can recognize many kinds of wood defects with high correct rate and efficiency.	cache/fcis-3173.pdf	txt/fcis-3173.txt