[1] SUN Y, CHEN Y H, WANG X G, et al. Deep learning face repersentation by joint identification-verification[J]. Advance in Neural Information Processing Systems, 2014, 27(12):30-60.
[2] LLORCA D F, ARROYO R, SOTELO M A. Vehicle logo recognition in traffic images HOG features and SVM[C]//2013 16th International IEEE Conference on Intelligent transportation Systems: Intelligent Transportation Systems for All M-odes(ITSC 2013).New York, USA: IEEE, 2014: 2229-2234.
[3] QIAN F. Face recognition based on PCA[D]. Nanjing: Southeast University, 2003: 49-51(in Chinese).
[4] XU P, FU H. Facial expression recognition based on convolutional neural network, [J]. Artificial Intelligence, 2015, 34(12):45-47(in Chinese).
[5] XU F J, WU W, GONG Y, et al. Tracking using convolutional neural networks[J]. IEEE Transcations on Neural Networks, 2010, 21(10):1610-1623. doi: 10.1109/TNN.2010.2066286
[6] BELHUMEUR P N, HESPANHA J P, KRIEGMAN D J. Recognition using class specific linear projection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(7):711-720. doi: 10.1109/34.598228
[7] ZHANG C, ZHANG Z. Improving multiview face detection with multi-task deep convolutional neural networks[C]//2014 IEEE Winter Conference on Application of Computer Vision(WACV). New York, USA: IEEE, 2014: 1036-1041.
[8] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. ImageNet classification with deep convolutional neural networks[C]//International Conference on Neural Information Processing Systems. City of North Miami Beach, Florida, USA: Curran Associates Inc., 2012: 1097-1105.
[9] BENGIO Y. Learning deep arcjitectures for AI[J]. Foundations & Trends® in Machine Learning, 2009, 2(1):1-127.
[10] LIN Y M. face recognition based on deep learning[D]. Dalian: Dalian University of Technology, 2013: 14-26(in Chinese).
[11] SUN Y, WANG X G, TANG X. Deep learning face representation form predicting 10, 000 classes[C]//Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. New York, USA: IEEE, 2014: 1891-1898.
[12] ZHENG Y, CHEN Q Q. Deep lesrning and its new progress in object and behavior recogntion[J]. Journal of Image and Graphic, 2014, 19(2):175-184.
[13] CHEN Ch. Research and implementation of face detection algorithm based on depth learning[D]. Chengdu: University of Electronic Science and Technology, 2017: 49-80(in Chinese).
[14] LANGKVISE M, KARLSSON L, LOU T A. Areview of unsuper vised feature learning and deep learning for time series modeling[J]. Pattern Recognition Letter, 2014, 42(5):11-24.
[15] XIONG Y, ZUO X Q, HUANG L, et al. Classification of color remote sensing images based on multi-feature combination[J]. Laser Technology, 2014, 38(2):165-171(in Chinese).
[16] LIU B. Infrared face recognition method based on random projection and sparse representation[D]. Xi'an: Xi'an Electronic and Science University, 2009: 2-9(in Chinese).
[17] SUN J G, MENG F Y. A weighted weighted fusion face recognition algorithm[J]. Journal of Intelligent Systems, 2015, 12(7):4-7(in Chinese).
[18] ZHANG B, LIU J F, TANG X L. Multi-scale video text detection based on corner and stroke width verification[C]//Visual Communications and Image Processing (VCIP), 2013. New York, USA: IEEE, 2014: 1-6.
[19] ZOU G F, FU G X. Multi pose face recognition based on weighted mean face[J]. Computer Application Research, 2017, 11(7):1-7(in Chinese).
[20] CHAN T H, MA Y. A simple deep learning baseline for image classification[J]. IEEE Transactions on Image Processing, 2015, 11(4):10-17.