[1] Christopher M Bishop. Pattern Recognition and Machine Learning (Information Science and Statistics)[M]. New York:Springer, 2006.

[2] Vpnik V N, Chervonenkis A Ja. Theoey of Pattern Recognition[M]. New York: Springer, 1974.

[3] 于筱川. 基于机器学习的车辆目标识别方法[D]. 西安: 西安电子科技大学, 2009.

    Yu Youchuan. Vehicle recognition method based on machine learning[D]. Xi′an: Xidian University, 2009. (in Chinese)

[4] 张全发, 蒲宝明, 李天然, 等. 基于HOG特征和机器学习的工程车辆检测[J]. 计算机系统应用, 2013, 22(7): 104-107.

    Zhang Quanfa, Pu Baoming, Li Tianran, et al. Vehicles detection based on histograms of oriented gradients and machine learning[J]. Computer Systems & Applications, 2013, 22(7): 104-107. (in Chinese)

[5] 慕春雷. 基于HOG特征的人脸识别系统研究[D]. 成都: 电子科技大学, 2013.

    Mu Chunlei. The research of face recognition system based on HOG feature[D]. Chengdu: University of Electronic Science and Technology of China, 2013. (in Chinese)

[6] 赵磊, 王斌, 张立明. 基于分割窗半监督支持向量机的遥感图像变化检测[J]. 复旦学报(自然科学版), 2010, 49(2): 190-196.

    Zhao Lei, Wang Bing, Zhang Liming. Change detection for remotely sensed images based on split window and semi-supervised SVM[J]. Journal of Fudan University(Natural Science), 2010, 49(2): 190-196. (in Chinese)

[7] 王鹏, 吕高杰, 龚俊斌, 等. 一种复杂海天背景下的红外舰船目标自动检测方法[J]. 武汉大学学报 信息科学版, 2011, 36(12): 1438-1441. (in Chinese)

    Wang Peng, Lv Gaojie, Gong Junbin, et al. An automatic target detection method for infrared ship in complex sea-sky background[J]. Geomatics and Information Science of Wuhan University, 2011, 36(12): 1438-1441. (in Chinese)

[8] Dalal Navneet, Triggs Bill. Histograms of oriented gradients for human detection[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, 1: 886-893.

[9] Carl Vondrick, Aditya Khosla, Tomasz Malisiewicz, et al. HOGgles: Visualizing Object Detection Features[C]// 2013 IEEE International Conference on Computer Vision (ICCV), 2013, 1: 1-8.

[10] Cortes C, Vapnik V N. Support vector networks[J]. Machine Learning, 1995, 20(3): 273-297.

[11] Webb G I, Ting K M. On the application of ROC analysis to predict classification performance under varying class distribution [J]. Machine Learning, 2005, 58(1): 2.