Wei Fang1,2, Feihong Zhang1,*, Victor S. Sheng3, Yewen Ding1
CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 167-178, 2018, DOI:10.32604/cmc.2018.02356
Abstract Image recognition has always been a hot research topic in the scientific community and industry. The emergence of convolutional neural networks(CNN) has made this technology turned into research focus on the field of computer vision, especially in image recognition. But it makes the recognition result largely dependent on the number and quality of training samples. Recently, DCGAN has become a frontier method for generating images, sounds, and videos. In this paper, DCGAN is used to generate sample that is difficult to collect and proposed an efficient design method of generating model. We combine DCGAN with More >
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