Electronics Optics & Control, Volume. 22, Issue 9, 77(2015)
Deep Classification Networks and Its Application in Intelligent Video Surveillance System
[2] [2] XU T, LIU H, QIAN Y L, et al. A novel method for people and vehicle classification based on Hough line feature [C ] //Proceedings of International Conference on Information Science and Technology (ICIST ), 2011 :240-245.
[3] [3] RIVLIN E, RUDZSKY M, GOLDENBERG R, et al. A re-
[4] [4] BOGOMOLOV Y, DROR G, LAPCHEV S, et al. Classification of moving targets based on motion and appearance [C]//Proceedings of British Machine Vision Conference (BMVC), 2003, 2:429-438.
[5] [5] TOYH D, ACH T. Detection and recognition of moving objects using statistical motion detection and Fourier scriptors [ C J//Proceedings of 12th International Conference on Image Analysis and Processing, 2003 :430-435.
[8] [8] HINTON G, SALAKHUTDINOV R R. Reducing the dimen-sionality o£ data with neural networks [J]. Science, 2006, 313(5786) :504-507.
[9] [9] HINTON G E, OSINDERO S, THE Y W. A fast learning algorithm for deep belief nets [ J ]. Neural Computation, 2006, 18(7) : 1527-1554.
[10] [10] BENGIO Y, COURVILLE A, VINCENT P. Representation learning: a review and new perspective [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(8) : 1798-1828.
[11] [11] KRIZHEVSKY A, SUTSKEVER I, HINTON G. ImageNet classification with deep convolutional neural networks [C ] //Proceedings of Neural Information and Processing Systems, 2012:1097-1105.
[12] [12] FARABET C, COUPRIEC, NAJMAN L, et al. Learning hi-erarchical features for scene labeling[ J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(8) : 1915-1929.
[13] [13] BORDES A, GLOROT X, WESTON J, et al. Joint learning of words and meaning representations for open-text semantic parsing[ C] //Proceedings of 15th International
[14] [14] SOCHER R, HUANG E H, PENNINGTON J, et al. Dynamic pooling and unfolding recursive autoencoders for paraphrase detection [ C ] //Proceedings of Neural Information and Processing Systems, 2011 : 801-809.
[15] [15] 10 Breakthrough Technologies 2013 [ Z]. MIT Technology Review, 2013.
[16] [16] INRIA. INRIA Person Dataset [ EB/OL]. (2005-01-01) [2014-01-01]. http://pascal, inrialpes. £r/data/human/.
[17] [17] MIT. MIT Pedestrian Data[EB/OL]. (2000-01-01) [2014- 01-01 ]. http: //cbcl. mit. edu/software-datasets/Pedestri- anData. html.
[18] [18] Caltech. Caltech Pedestrian Detection Benchmark [ EB/ OL]. (2009-01-01) [2014-01-01 ]. http: //www. vision, caltech. edu/Image_Datasets/ CaltechPedestrians/.
[19] [19] BELHUMEUR P N, HESPANHA J P, KRIEGMAN D J. Eigenfaces vs fisherfaces: recognition using class specific linear projection] J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(7) :711-720.
[20] [20] JIANG Z LIN Z, DAVIS S. Label consistent K-SVD:learning a discriminative dictionary for recognition [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(11) :2651-2664.
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SUN Ning, CHEN Liang, HAN Guang, LI Xiao-fei. Deep Classification Networks and Its Application in Intelligent Video Surveillance System[J]. Electronics Optics & Control, 2015, 22(9): 77
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Received: Oct. 29, 2014
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Published Online: Jan. 28, 2021
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