[1] Sang Jianhua, Zhang Zongbin. Infrared stealth technology development trend [J]. Infrared and Laser Engineering, 2013, 42(1): 14-19. (in Chinese)

     Sang Jianhua, Zhang Zongbin. Infrared stealth technology development trend [J]. Infrared and Laser Engineering, 2013, 42(1): 14-19. (in Chinese)

[2] Han Yuge, Xuan Yimin. The methodology study for the infrared camouflage effect evaluating of the armored vehicle[J]. Infrared Technology, 2003, 25(6): 22-24. (in Chinese)

     Han Yuge, Xuan Yimin. The methodology study for the infrared camouflage effect evaluating of the armored vehicle[J]. Infrared Technology, 2003, 25(6): 22-24. (in Chinese)

[3] Gao Yuan, Liu Jian, Zhang Junju, et al. Research on infrared stealth effect assessment method for weapons and equipment [J]. Infrared Technology, 2017, 39(11):1060-1065. (in Chinese)

     Gao Yuan, Liu Jian, Zhang Junju, et al. Research on infrared stealth effect assessment method for weapons and equipment [J]. Infrared Technology, 2017, 39(11):1060-1065. (in Chinese)

[4] Tian Hongbin. Infrared small target detection based on bilateral filtering and bahiti distance [J]. Nuclear Electronics & Detection Technology, 2014(10): 1159-1163. (in Chinese)

     Tian Hongbin. Infrared small target detection based on bilateral filtering and bahiti distance [J]. Nuclear Electronics & Detection Technology, 2014(10): 1159-1163. (in Chinese)

[5] Jin Guangzhi, Shi Linsuo, Liu Junchao, et al. Image matching algorithm based on neighborhood weighting and RGB color component [J]. Infrared Technology, 2016, 38(3): 225-229. (in Chinese)

     Jin Guangzhi, Shi Linsuo, Liu Junchao, et al. Image matching algorithm based on neighborhood weighting and RGB color component [J]. Infrared Technology, 2016, 38(3): 225-229. (in Chinese)

[6] Liu Xuehai. Real-time infrared image matching algorithm research and implementation [D]. Beijing: Beijing University of Posts and Telecommunications, 2014: 15-27. (in Chinese)

     Liu Xuehai. Real-time infrared image matching algorithm research and implementation [D]. Beijing: Beijing University of Posts and Telecommunications, 2014: 15-27. (in Chinese)

[7] Yuan Wanli, Li Chaofeng. No-reference fuzzy image evaluation method combined with HVS and SSIM [J]. Computer Engineering and Applications, 2013, 49(1):210-212. (in Chinese)

     Yuan Wanli, Li Chaofeng. No-reference fuzzy image evaluation method combined with HVS and SSIM [J]. Computer Engineering and Applications, 2013, 49(1):210-212. (in Chinese)

[8] Dalal Navneet, Triggs Bill. Histograms of oriented gradientsfor human detection[C]//IEEE Computer Society conferenceon computer vision and pattern recognition, 2005, 1: 886 -893.

     Dalal Navneet, Triggs Bill. Histograms of oriented gradientsfor human detection[C]//IEEE Computer Society conferenceon computer vision and pattern recognition, 2005, 1: 886 -893.

[9] Zhang Difei, Zhang Jinsuo, Yao Keming, et al. Infrared ship target recognition based on SVM classification [J]. Infrared and Laser Engineering, 2016, 45(1): 0104004. (in Chinese)

     Zhang Difei, Zhang Jinsuo, Yao Keming, et al. Infrared ship target recognition based on SVM classification [J]. Infrared and Laser Engineering, 2016, 45(1): 0104004. (in Chinese)

[10] Zheng Zeyu, Gu Siyu. TensorFlow′s Actual Google Deep Learning Framework[M]. Beijing: Publishing House of Electronics Industry, 2017: 155-168. (in Chinese)

     Zheng Zeyu, Gu Siyu. TensorFlow′s Actual Google Deep Learning Framework[M]. Beijing: Publishing House of Electronics Industry, 2017: 155-168. (in Chinese)

[11] Liu Feng, Shen Tongsheng, Ma Xinxing, et al. Ship target recognition based on multi-band deep neural network [J]. Optics and Precision Engineering, 2017, 25(11): 2939-2946. (in Chinese)

     Liu Feng, Shen Tongsheng, Ma Xinxing, et al. Ship target recognition based on multi-band deep neural network [J]. Optics and Precision Engineering, 2017, 25(11): 2939-2946. (in Chinese)

[12] Luo Jiaxiang, Lin Changhe, Wang Jiapeng, et al. Accurate image localization based on deep convolutional network and accelerated robust feature registration [J]. Optics and Precision Engineering, 2017, 25(2): 469-476. (in Chinese)

     Luo Jiaxiang, Lin Changhe, Wang Jiapeng, et al. Accurate image localization based on deep convolutional network and accelerated robust feature registration [J]. Optics and Precision Engineering, 2017, 25(2): 469-476. (in Chinese)

[13] Lea C, Reiter A, Vidal R, et al. Segmental spatiotemporal CNNs for fine-grained action segmentation [C]//Computer Vision-ECCV 2016, 2016: 36-52.

     Lea C, Reiter A, Vidal R, et al. Segmental spatiotemporal CNNs for fine-grained action segmentation [C]//Computer Vision-ECCV 2016, 2016: 36-52.

[14] Colin Lea, Michael D Flynn, Rene Vidal, et al. Temporal convolutional networks for action segmentation and detection [C]//Computer Vision and Patten Recognition, 2016:1003-1012.

     Colin Lea, Michael D Flynn, Rene Vidal, et al. Temporal convolutional networks for action segmentation and detection [C]//Computer Vision and Patten Recognition, 2016:1003-1012.

[15] Wang Zhongmei, Yang Xiaomei, Gu Xingfa. Infrared image small target detection based on robust principal component analysis [J]. Journal of Ordnance, 2016, 37(9): 1753-1760. (in Chinese)

     Wang Zhongmei, Yang Xiaomei, Gu Xingfa. Infrared image small target detection based on robust principal component analysis [J]. Journal of Ordnance, 2016, 37(9): 1753-1760. (in Chinese)

[16] Tu Shan, Zhang Wentao, Xiong Xianming, et al. Principal component analysis of transgenic cotton seeds based on terahertz time-domain spectroscopy [J]. Acta Photonica Sinica, 2015, 44(4): 176-181. (in Chinese)

     Tu Shan, Zhang Wentao, Xiong Xianming, et al. Principal component analysis of transgenic cotton seeds based on terahertz time-domain spectroscopy [J]. Acta Photonica Sinica, 2015, 44(4): 176-181. (in Chinese)