[1] Fu Min, Wang Wei, Wang Hao. Application of multi classification sup-port vector machine in transit transfer recognition[J]. Journal of Harbin Institute of Technology, 50, 26-32(2018).

[2] Gu J, Wang Z, Kuen J. Recent advances in convolutional neural networks[J]. Pattern Recognition, 77, 354-377(2018).

[3] Modarres M H, Aversa R, Cozzini S. Neural network for nanoscience scanning electron microscope image recognition[J]. Scientific Reports, 7, 1-12(2017).

[4] [4] Mohapatra R K, Majhi B, Jena S K, Classification perfmance analysis of MNIST dataest utilizing a multiresolution, technique[C]Computing, Communication Security (ICCC S), 2015 Internationl Conference on. IEEE2015: 15.

[5] Cai Huaiyu, Wu Xiaoyu, Zhuo Liran. Fast sift image mosaic method combined with edge detection[J]. Infrared and Laser Engineering, 47, 1126003(2018).

[6] Wang Jiping, Zhi Xiaorong, Hang Jihong. Analysis of forest landscape pattern grade characteristics based on GIS and PCA dimension reduction[J]. Transactions of the Chinese Society for Agricultural Machinery, 50, 195-201+179(2019).

[7] Zhou Feiyan, Jin Linpeng, Dong Jun. A review of convolutional neural networks[J]. Chinese Journal of Computers, 40, 1229-1251(2017).

[8] Wang Hongxia, Zhou Jiaqi, Gu Chenghao. Design of activation function inconvolution neu-ral network for image classification[J]. Journal of Zhejiang University (Engineering Science), 53, 1363-1373(2019).

[9] Wu Yunxia, Tian Yimin. Recognition method of coal and rock based on maximum pool sparse coding[J]. Chinese Journal of Engineering, 39, 981-987(2017).

[10] Liang Minjian, Cui Xiaoyu, Song Qingsong. Traffic sign recognition met -hod based on hog Gabor feature fusion and softmax classifier[J]. Journal of Traffic and Transportation Engineering, 17, 151-158(2017).

[11] Wang Jun, Zheng Tong, Lei Peng. Recognition method of gesture action radar based on convolutional neural network[J]. Journal of Beijing University of Aeronautics and Astronautics, 44, 1117-1123(2018).

[12] Zheng Yili, Zhang Lu. Plant leaf image recognition method based on convolution neural network of transfer learning[J]. Transactions of the Chinese Society for Agricultural Machinery, 49, 354-359(2018).

[13] Long Mansheng, Ouyang Chunjuan, Liu Huan. Image recognition of oil tea disease based on convolution neural network and migration learning[J]. Transactions of the Chinese Society of Agricultural Engineering, 34, 194-201(2018).

[14] Liu Qiong, Li Zongxian, Sun Fuchun. Image recognition and classification based on deep belief convolution neural network[J]. Tsinghua Science and Technology, 58, 781-787(2018).