[1] WangX, Zheng SF, YangR, et al. ( 2019-01-22)[2019-04-18]. https:∥arxiv.gg363.site/abs/1901. 07474.

[2] 赵建堂. 基于深度学习的单幅图像去雾算法[J]. 激光与光电子学进展, 2019, 56(11): 111005.

    Zhao J T. Single-image defogging algorithm based on deep learning[J]. Laser & Optoelectronics Progress, 2019, 56(11): 111005.

[3] LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 2015, 521(7553): 436-444.

[4] 李亚鹏, 万遂人. 基于深度学习的行人属性多标签识别[J]. 中国生物医学工程学报, 2018, 37(4): 423-428.

    Li Y P, Wan S R. Multi-label recognition of pedestrian attributes based on deep learning[J]. Chinese Journal of Biomedical Engineering, 2018, 37(4): 423-428.

[5] Li DW, Chen XT, Huang KQ. Multi-attribute learning for pedestrian attribute recognition in surveillance scenarios[C]∥2015 3rd IAPR Asian Conference on Pattern Recognition (ACPR), November 3-6, 2015, Kuala Lumpur, Malaysia. New York: IEEE, 2015: 111- 115.

[6] Li YN, HuangC, Loy CC, et al. Human attribute recognition by deep hierarchical contexts[M] ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 2016, 9910: 684- 700.

[7] Liu XH, Zhao HY, Tian MQ, et al. HydraPlus-Net: attentive deep features for pedestrian analysis[C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 2017: 350- 359.

[8] Wang JY, Zhu XT, Gong SG, et al. Attribute recognition by joint recurrent learning of context and correlation[C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 2017: 531- 540.

[9] 凌弘毅. 基于知识蒸馏方法的行人属性识别研究[J]. 计算机应用与软件, 2018, 35(10): 181-184, 193.

    Ling H Y. Pedestrian attribute recognition based on knowledge distillation[J]. Computer Applications and Software, 2018, 35(10): 181-184, 193.

[10] Song CF, HuangY, Ouyang WL, et al. Mask-guided contrastive attention model for person re-identification[C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 2018: 1179- 1188.

[11] He KM, Zhang XY, Ren SQ, et al. Deep residual learning for image recognition[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 770- 778.

[12] 李净, 管业鹏. 基于深度学习行人属性自适应权重分配行人再识别方法[J]. 激光与光电子学进展, 2019, 56(14): 141003.

    Li J, Guan Y P. Pedestrian re-identification based on adaptive weight assignment using deep learning for pedestrian attributes[J]. Laser & Optoelectronics Progress, 2019, 56(14): 141003.

[13] 张超, 陈莹. 残差网络下基于困难样本挖掘的目标检测[J]. 激光与光电子学进展, 2018, 55(10): 101003.

    Zhang C, Chen Y. Object detection based on hard examples mining using residual network[J]. Laser & Optoelectronics Progress, 2018, 55(10): 101003.

[14] Chen L C, Papandreou G, Kokkinos I, et al. DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40(4): 834-848.

[15] 裴亮, 刘阳, 高琳. 结合全卷积神经网络与条件随机场的资源3号遥感影像云检测[J]. 激光与光电子学进展, 2019, 56(10): 102802.

    Pei L, Liu Y, Gao L. Cloud detection of ZY-3 remote sensing images based on fully convolutional neural network and conditional random field[J]. Laser & Optoelectronics Progress, 2019, 56(10): 102802.

[16] 郭呈呈, 于凤芹, 陈莹. 基于卷积神经网络特征和改进超像素匹配的图像语义分割[J]. 激光与光电子学进展, 2018, 55(8): 081005.

    Guo C C, Yu F Q, Chen Y. Image semantic segmentation based on convolutional neural network feature and improved superpixel matching[J]. Laser & Optoelectronics Progress, 2018, 55(8): 081005.

[17] Deng YB, LuoP, Loy CC, et al. Pedestrian attribute recognition at far distance[C]∥Proceedings of the ACM International Conference on Multimedia-MM '14, November 3-7, 2014, Orlando, Florida, USA. New York: ACM, 2014: 789- 792.

[18] Li DW, Chen XT, ZhangZ, et al. Pose guided deep model for pedestrian attribute recognition in surveillance scenarios[C]∥2018 IEEE International Conference on Multimedia and Expo (ICME), July 23-27, 2018, San Diego, CA, USA. New York: IEEE, 2018: 18163829.

[19] Li DW, ZhangZ, Chen XT, et al. ( 2016-04-27)[2019-04-18]. https:∥arxiv.gg363.site/abs/1603. 07054.

[20] YuK, LengB, ZhangZ, et al. and localization[J/OL]. ( 2016-11-17)[2019-04-18]. https:∥arxiv.gg363.site/abs/1611. 05603.

[21] SudoweP, SpitzerH, LeibeB. Person attribute recognition with a jointly-trained holistic CNN model[C]∥2015 IEEE International Conference on Computer Vision Workshop (ICCVW), December 7-13, 2015, Santiago, Chile. New York: IEEE, 2015: 329- 337.