[1] Zhao Y Y, Chang J D[J]. Detection and handling of drones in low altitude airspace Electronic Warfare, 2016, 44-49.

[2] Li C L, Wang X, Zhang L et al. Weighted low-rank decomposition for robust grayscale-thermal foreground detection[J]. IEEE Transactions on Circuits and Systems for Video Technology, 27, 725-738(2016). http://ieeexplore.ieee.org/document/7457366/

[3] Li C L, Wang G Z, Ma Y P, a novel approach[J/OL] et al. -01-11)[2019-07-02], org/abs/1701, 02829(2017). https://arxiv.

[4] Ha Q S, Watanabe K, Karasawa T et al. MFNet: towards real-time semantic segmentation for autonomous vehicles with multi-spectral scenes. [C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 24-28, 2017, Vancouver, BC, Canada. New York: IEEE, 5108-5115(2017).

[5] Zhai S L, Shao P P, Liang X Y et al. Fast RGB-T tracking via cross-modal correlation filters[J]. Neurocomputing, 334, 172-181(2019).

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

[7] Dai J F, Li Y, He K M et al. R-FCN: object detection via region-based fully convolutional networks. [C]//Advances in Neural Information Processing Systems, December 5-10, 2016, Barcelona, Spain. Canada: NIPS, 379-387(2016).

[8] Xie J R, Li F M, Wei H et al. Enhancement of single shot multibox detector for aerial infrared target detection[J]. Acta Optica Sinica, 39, 0615001(2019).

[9] Redmon J, Divvala S, Girshick R 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, 779-788(2016).

[10] Redmon J. -04-08)[2019-07-02][J/OL]. Farhadi A. Yolov3: an incremental improvement., org/abs/1804, 02767(2018). https://arxiv.

[11] Rozantsev A, Lepetit V, Fua P. Flying objects detection from a single moving camera. [C]//2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 4128-4136(2015).

[12] Du L, Gao C Q, Feng Q et al. Small UAV detection in videos from a single moving camera[M]. //Yang J F, Hu Q H, Cheng M M, et al. Computer vision. CCCV 2017. Communications in computer and information science. Singapore: Springer, 773, 187-197(2017).

[13] Wang J Y, Wang X Y, Zhang K et al. Small UAV target detection model based on deep neural network[J]. Journal of Northwestern Polytechnical University, 36, 258-263(2018).

[14] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]//The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, USA. New York: IEEE, 770-778(2015).

[15] [15] IoffeS, SzegedyC. Batch normalization: accelerating deep network training by reducing internal covariate shift[C]//Proceedings of the 32nd International Conference on International Conference on Machine Learning, July 6-11, 2015, Lille, France. USA: MIT Press, 2015, 37: 448- 456.

[16] 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, 56, 041502(2019).

[17] Redmon J, Farhadi A. 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, 6517-6525(2017).

[18] Wang J D, Wei Z, Zhang T et al. -05-25)[2019-07-02], org/abs/1605, 07716(2016). https://arxiv.

[19] Wei Y M, Quan J C, Houyu Q Y. Aerial image location of unmanned aerial vehicle based on YOLO v2[J]. Laser & Optoelectronics Progress, 54, 111002(2017).