[1] 王文秀, 傅雨田, 董峰, 等. 基于深度卷积神经网络的红外船只目标检测方法[J]. 光学学报, 2018, 38(7): 0712006.

    Wang W X, Fu Y T, Dong F, et al. Infrared ship target detection method based on deep convolution neural network[J]. Acta Optica Sinica, 2018, 38(7): 0712006.

[2] 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.

[3] GirshickR, DonahueJ, DarrellT, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 2014: 14632381.

[4] Sun X D, Wu P C. Hoi S C H. Face detection using deep learning: an improved Faster RCNN approach[J]. Neurocomputing, 2018, 299: 42-50.

[5] 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.

[6] 杜兰, 刘彬, 王燕, 等. 基于卷积神经网络的SAR图像目标检测算法[J]. 电子与信息学报, 2016, 38(12): 3018-3025.

    Du L, Liu B, Wang Y, et al. Target detection method based on convolutional neural network for SAR image[J]. Journal of Electronics & Information Technology, 2016, 38(12): 3018-3025.

[7] KangM, Leng XG, LinZ, et al. A modified Faster R-CNN based on CFAR algorithm for SAR ship detection[C]∥2017 International Workshop on Remote Sensing with Intelligent Processing (RSIP), May 18-21, 2017, Shanghai, China. New York: IEEE, 2017: 16981074.

[8] 李健伟, 曲长文, 彭书娟, 等. 基于卷积神经网络的SAR图像舰船目标检测[J]. 系统工程与电子技术, 2018, 40(9): 1953-1959.

    Li J W, Qu C W, Peng S J, et al. Ship detection in SAR images based on convolutional neural network[J]. Systems Engineering and Electronics, 2018, 40(9): 1953-1959.

[9] 侯冰基, 杨明辉, 孙晓玮. 基于改进Faster RCNN的毫米波图像实时目标检测[J]. 激光与光电子学进展, 2019, 56(13): 131009.

    Hou B J, Yang M H, Sun X W. Real-time object detection for millimeter-wave images based on improved faster regions with convolutional neural networks[J]. Laser & Optoelectronics Progress, 2019, 56(13): 131009.

[10] 冯小雨, 梅卫, 胡大帅. 基于改进Faster R-CNN的空中目标检测[J]. 光学学报, 2018, 38(6): 0615004.

    Feng X Y, Mei W, Hu D S. Aerial target detection based on improved Faster R-CNN[J]. Acta Optica Sinica, 2018, 38(6): 0615004.

[11] 任之俊, 蔺素珍, 李大威, 等. 基于改进特征金字塔的Mask R-CNN目标检测方法[J]. 激光与光电子学进展, 2019, 56(4): 041502.

    Ren Z J, Lin S Z, Li D W, et al. Mask R-CNN object detection method based on improved feature pyramid[J]. Laser & Optoelectronics Progress, 2019, 56(4): 041502.

[12] Chen Y C, Zhu X T, Zheng W S, et al. Person re-identification by camera correlation aware feature augmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40(2): 392-408.

[13] SimonyanK, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. ( 2015-04-10)[2019-10-13]. https:∥arxiv.org/abs/1409. 1556.

[14] 张松龙, 谢林柏. 基于级联全卷积神经网络的显著性检测[J]. 激光与光电子学进展, 2019, 56(7): 071501.

    Zhang S L, Xie L B. Salient detection based on cascaded convolutional neural network[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071501.