[1] Simonyan K, Parkhi O, Vedaldi A et al. Fisher vector faces in the wild. In Proc. Conf. British Machine Vision, September 2013.[2] Berg T, Belhumeur P N. POOF:Part-based one-vs-one features for fine-grained categorization, face verification, and attribute estimation. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2013, pp.955-962.[3] Cao Q, Ying Y, Li P. Similarity metric learning for face recognition. In Proc. IEEE Int. Conf. Computer Vision, January 2013, pp.2408-2415.[4] Sun Y, Wang X, Tang X. Deep learning face representation from predicting 10000 classes. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2014, pp.1891-1898.[5] Sun Y, Chen Y, Wang X et al. Deep learning face representation by joint identification-verification. In Proc. Int. Conf. Neural Information Processing Systems, November 2015, pp.1988-1996.[6] Feris R S, Siddiquie B, Petterson J et al. Large-scale vehicle detection, indexing, and search in urban surveillance videos. IEEE Trans. Multimedia, 2012, 14(1):28-42.[7] Hu C, Bai X, Qi L et al. Learning discriminative pattern for real-time car brand recognition. IEEE Trans. Intelligent Transportation Systems, 2015, 16(6):3170-3181.[8] Grauman K, Crandall D, Parikh D et al. Discovering localized attributes for fine-grained recognition. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2012, pp.3474-3481.[9] Wah C, Horn G V, Branson S et al. Similarity comparisons for interactive fine-grained categorization. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2014, pp.859-866.[10] Goering C, Rodner E, Freytag A et al. Nonparametric part transfer for fine-grained recognition. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2014, pp.2489-2496.[11] Krause J, Deng J, Stark M et al. Collecting a large-scale dataset of fine-grained cars. In Proc. the 2nd Fine-Grained Visual Categorization Workshop, June 2013.[12] Yang L, Luo P, Chen C L et al. A large-scale car dataset for fine-grained categorization and verification. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2015, pp.3973-3981.[13] Krause J, Stark M, Deng J et al. 3D object representations for fine-grained categorization. In Proc. IEEE Int. Conf. Computer Vision, June 2013, pp.554-561.[14] Lin Y L, Morariu V I, Hsu W et al. Jointly optimizing 3D model fitting and fine-grained classification. In Proc. European Conference on Computer Vision, September 2014, pp.466-480.[15] Stark M, Krause J, Pepik B et al. Fine-grained categorization for 3D scene understanding. In Proc. Conf. British Machine Vision, September 2012, pp.228-236.[16] Sochor J, Herout A, Havel J. BoxCars:3D boxes as CNN input for improved fine-grained vehicle recognition. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2016, pp.3006-3015.[17] Zhang X, Zhou F, Lin Y et al. Embedding label structures for fine-grained feature representation. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2016, pp.1114-1123.[18] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. In Proc. Int. Conf. Neural Information Processing Systems, November 2012, pp.1097-1105.[19] He H, Shao Z, Tan J. Recognition of car makes and models from a single traffic-camera image. IEEE Trans. Intelligent Transportation Systems, 2015, 16(6):3182-3192.[20] Chan T H, Jia K, Gao S et al. PCANet:A simple deep learning baseline for image classification? IEEE Trans. Image Processing, 2014, 24(12):5017-5032.[21] Dong Z, Wu Y, Pei M et al. Vehicle type classification using a semi supervised convolutional neural network. IEEE Trans. Intelligent Transportation Systems, 2015, 16(4):2247-2256.[22] Xie S, Yang T, Wang X et al. Hyper-class augmented and regularized deep learning for fine-grained image classification. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2015, pp.2645-2654.[23] Zhao B, Wu X, Feng J et al. Diversified visual attention networks for fine-grained object classification. IEEE Trans. Multimedia, 2017, 19(6):1245-1256.[24] Zia M Z, Stark M, Schindler K. Towards scene understanding with detailed 3D object representations. International Journal of Computer Vision, 2015, 112(2):188-203.[25] Arandjelovic R, Zisserman A. Three things everyone should know to improve object retrieval. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2012, pp.2911-2918.[26] Dalal N, Triggs B. Histograms of oriented gradients for human detection. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2005, pp.886-893.[27] Chen T, Chen Z, Shi Q et al. Road marking detection and classification using machine learning algorithms. In Proc. Intelligent Vehicles Symp., June 2015, pp.617-621.[28] Wang X S, Cai C. Weed seeds classification based on PCANet deep learning baseline. In Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, December 2015, pp.408-415.[29] Wu J, Shi J, Li Y et al. Histopathological image classification using random binary hashing based PCANet and bilinear classifier. In Proc. Conf. European Signal Processing, August 2016, pp.2050-2054.[30] Xia Y, Li J, Qi L et al. Loop closure detection for visual SLAM using PCANet features. In Proc. Int. Conf. Neural Networks, July 2016, pp.2274-2281.[31] Jia H, Sun Q, Wang T. PCANet for blind image quality assessment. In Proc. Int. Conf. Computational Intelligence and Security, December 2015, pp.195-198.[32] Kwang K, Keechul J, Hang J K. Face recognition using kernel principal component analysis. IEEE Signal Processing Letters, 2002, 9(2):40-42.[33] Szegedy C, Liu W, Jia Y et al. Going deeper with convolutions. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 2014. |