3 Ren S Q, He K M, Girshick R, et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1137-1137.
DOI:
10.1109/TPAMI.2016.2577031
4 Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation[C]//Proceedings of 2015 IEEE Conference on Computer Vision and Pattern Recognition, 2015: 3431-3440.
5 Wang S F, Yan J H, Wang Z G. Improved moving object detection algorithm based on local united feature[J]. Chinese Journal of Scientific Instrument, 2015, 36(10): 2241-2248.
DOI:
10.3969/j.issn.0254-3087.2015.10.011
6 Liu W, Zhao W J, Li C, et al. Detecting small moving target based on the improved ORB feature matching[J]. Opto-Electronic Engineering, 2015, 42(10): 13-20.
DOI:
10.3969/j.issn.1003-501X.2015.10.003
8 Zhang J M, Wang B. Moving object detection under condition of fast illumination change[J]. Opto-Electronic Engineering, 2016, 43(2): 14-21.
DOI:
10.3969/j.issn.1003-501X.2016.02.003
10 Luo S, Jiang Y Z. State-of-art of video based smoke detection algorithms[J]. Journal of Image and Graphics, 2013, 18(10): 1225-1236.
DOI:
10.11834/jig.20131002
11 Shi L F, Long F, Zhan Y J, et al. Video-based fire detection with spatio-temporal SURF and color features[C]//Proceedings of 2016 12th World Congress on Intelligent Control and Automation, 2016: 258-262.
12 Dosovitskiy A, Fischery P, Ilg E, et al. Flownet: learning optical flow with convolutional networks[C]// Proceeding of 2015 IEEE International Conference on Computer Vision, 2015: 2758-2766.
13 Ilg E, Mayer N, Saikia T, et al. Flownet 2. 0: evolution of optical flow estimation with deep networks[C]//Proceeding of 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017: 1647-1655.
15 Ouyang P, Hu H, Shi Z Z. Plankton classification with deep convolutional neural networks[C]//Proceeding of 2016 IEEE Information Technology, Networking, Electronic and Automation Control Conference, 2016: 132-136.
16 He K M, Zhang X Y, Ren S Q, et al. Deep residual learning for image recognition[C]//Proceeding of 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016: 770-778.
17 He K M, Zhang X Y, Ren S Q, et al. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification[C]//Proceeding of 2015 IEEE International Conference on Computer Vision, 2015: 1026-1034.
18 He K M, Sun J. Convolutional neural networks at constrained time cost[C]//Proceeding of 2015 IEEE Conference on Computer Vision and Pattern Recognition, 2015: 3992-4000.
20 Lucas B D, Kanade T. An iterative image registration technique with an application to stereo vision (DARPA)[C]//Proceedings of the 1981 DARPA Image Understanding Workshop, 1981: 121-130.
