[1] 叶国林, 孙韶媛, 高凯珺, 等. 基于加速区域卷积神经网络的夜间行人检测研究[J]. 激光与光电子学进展, 2017, 54(8): 081003.

    Ye G L, Sun S Y, Gao K J, et al. Nighttime pedestrian detection based on faster region convolution neural network[J]. Laser & Optoelectronics Progress, 2017, 54(8): 081003.

[2] 陆永帅, 李元祥, 刘波, 等. 基于深度残差网络的高光谱遥感数据霾监测[J]. 光学学报, 2017, 37(11): 1128001.

    Lu Y S, Li Y X, Liu B, et al. Hyperspectral data haze monitoring based on deep residual network[J]. Acta Optica Sinica, 2017, 37(11): 1128001.

[3] 王正来, 黄敏, 朱启兵, 等. 基于并行深度残差网络的堆场烟雾检测方法[J]. 激光与光电子学进展, 2018, 55(5): 051008.

    Wang Z L, Huang M, Zhu Q B, et al. Smoke detection in storage yard based on parallel deep residual network[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051008.

[4] Girshick R, Donahue J, Darrell T, et al. Region-based convolutional networks for accurate object detection and segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016, 38(1): 142-158.

[5] He K M, Zhang X Y, Ren S Q, et al. Spatial pyramid pooling in deep convolutional networks for visual recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(9): 1904-1916.

[6] Lin TY, DollárP, GirshickR, et al. Feature pyramid networks for object detection[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 17355379.

[7] GirshickR. Fast R-CNN[C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 2015: 1440- 1448.

[8] 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): 1137-1149.

[9] Dai JF, LiY, He KM, et al. R-FCN: object detection via region-based fully convolutional networks[C]∥ 30th Conference on Neural Information Processing Systems (NIPS 2016), December 5-10, 2016, Barcelona, Spain. USA: Curran Associates Inc., 2016: 379- 387.

[10] He KM, GkioxariG, DollárP, et al. Mask R-CNN[C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 2017: 2980- 2988.

[11] RedmonJ, FarhadiA. YOLO9000: better, faster, stronger[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 2017: 6517- 6525.

[12] RedmonJ, Farhadi A.Yolov3:an incrementalimprovement[J/OL].( 2018-04-08)[2018-11-16]. https:∥arxiv.org/abs/1804. 02767.

[13] LiuW, AnguelovD, ErhanD, et al. SSD: single shot MultiBox detector[M] ∥Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science, Cham: Springer, 2016, 9905: 21- 37.

[14] RedmonJ, DivvalaS, GirshickR, et al. You only look once: unified, real-time object detection[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 779- 788.

[15] Fu CY, LiuW, RangaA, et al. DSSD: deconvolutional single shot detector[J/OL]. ( 2017-01-23)[2018-11-16]. https:∥arxiv.org/abs/1701. 06659.

[16] 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.

[17] ShrivastavaA, GuptaA, GirshickR. Training region-based object detectors with online hard example mining[C]∥2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 2016: 761- 769.

[18] ShrivastavaM, MatlaniP. A smoke detection algorithm based on K-means segmentation[C]∥2016 International Conference on Audio, Language and Image Processing (ICALIP), July 11-12, 2016, Shanghai, China. New York: IEEE, 2016: 301- 305.