Mu Ye1,2,3,4, Li Ji1, Luo Tianye1, Li Sihan5, Zhang Tong1, Feng Ruilong1, Hu Tianli1,2,3,4, Gong He1,2,3,4, Guo Ying1,2,3,4, Sun Yu1,2,3,4, Thobela Louis Tyasi6, Li Shijun7,8,*
CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6195-6205, 2022, DOI:10.32604/cmc.2022.026880
Abstract Remote sensing image analysis is a basic and practical research hotspot in remote sensing science. Remote sensing images contain abundant ground object information and it can be used in urban planning, agricultural monitoring, ecological services, geological exploration and other aspects. In this paper, we propose a lightweight model combining vgg-16 and u-net network. By combining two convolutional neural networks, we classify scenes of remote sensing images. While ensuring the accuracy of the model, try to reduce the memory of the model. According to the experimental results of this paper, we have improved the accuracy of the model to 98%. The… More >
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