Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 202-206.doi: 10.11896/j.issn.1002-137X.2017.11A.042
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YAN Rong-hua, PENG Jin-ye and WEN De-sheng
[1] HYVARINEN A.Fast and robust fixed-point algorithms for independent component analysis [J].IEEE Transactions on Neural Networks,1999,0(3):626-634. [2] LOWE D.Distinctive image features from scale Invariant keypoints[J].IJCV,2004,60(2):91-110. [3] DALAL N,TRIGGS B.Histograms of oriented gradients forhuman detection[C]∥CVPR.2005. [4] CHENG H S,HU X F.The human body detection based on HOG and SVM technology research in static image[J].Chinese Journal of Scientific Instrument,2012,9(5):20-23. [5] KRIZHEVSKY A,SUTSKEVER I,HINTON G E.Image netclassification with deep convolutional neural networks [C]∥Advances in Neural Information Processing Systems.2012:1097-1105. [6] HINTON G E,SALAKHUTDINOV R.Reducing dimensionality of data with neural networks[J].Science,2006(504):313. [7] BENGIO Y,COURVILLE A C,VINCENT P.Unsupervisedfeature learning and deep learning:A review and new perspectives [J].CoRR abs/1206 2012.5538. [8] SERMANET P,KAVUKCUOGLU K,CHINTALA S,et al.Pedestrian detection with unsupervised and multi-stage feature learning[C]∥CVPR.2013. [9] ENZWEILER M,EIGENSTETTER A,Schiele B.Multi-cue pedestrian classification with partial occlusion handling[C]∥CVPR.2010. [10] VIOLA P,JONES M J,SNOW D.Detecting pedestrians using patterns of motion and appearance[C]∥IJCV.2005:153-161. [11] 田仙仙,鲍泓,徐成.一种改进HOG特征的行人检测算法[J].计算机科学,2014,41(9):237-259. |
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