id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-20810	Hua, Weiqi; Li, Chunzhong; Wang, Xinsheng	Review of Convolutional Neural Network Models and Image Classification	2024	7	.pdf	application/pdf	5150	214	40	In this paper, we review the research background, significance and current research status of convolutional neural network model and image classification, study two image classification methods based on ResNet and ShuffleNet, and provide a comprehensive review of the construction methods and characteristics of the two deep convolutional neural network model structures, and finally compare and analyse the performance of the two classification models. Traditional image classification methods are difficult to deal with the huge image data, and cannot meet the requirements of people on the accuracy and speed of image classification, the image classification method based on convolutional neural network breaks through the bottleneck of the traditional image classification method, and becomes the mainstream algorithm of image classification, how to effectively use convolutional neural network to classify images has become a hot spot of research in the field of computer vision at home and abroad.	cache/ajst-20810.pdf	txt/ajst-20810.txt