[1] Aguilar W G, Luna M A, Moya J F et al. Pedestrian detection for UAVs using cascade classifiers with meanshift. [C]∥2017 IEEE 11th International Conference on Semantic Computing (ICSC), January 30-February 1, 2017, San Diego, CA, USA. New York: IEEE, 509-514(2017).
[2] Yuan C, Liu Z X, Zhang Y M. UAV-based forest fire detection and tracking using image processing techniques. [C]∥2015 International Conference on Unmanned Aircraft Systems (ICUAS), June 9-12, 2015, Denver, CO, USA. New York: IEEE, 639-643(2015).
[3] Xu Y Z, Yu G Z, Wang Y P et al. Car detection from low-altitude UAV imagery with the faster R-CNN[J]. Journal of Advanced Transportation, 2017, 2823617(2017).
[4] Dalal N, Triggs B. Histograms of oriented gradients for human detection. [C]∥2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), June 20-25, 2005, San Diego, CA, USA. New York: IEEE, 8588935(2005).
[7] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks. [C]∥Advances in Neural Information Processing Systems, December 7-12, 2015, Montreal, Quebec, Canada. Canada: NIPS, 91-99(2015).
[8] Dai J, 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).
[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, 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).
[12] Liu W, Anguelov D, Erhan D 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, 9905, 21-37(2016).
[15] Lin T Y, Goyal P, Girshick R et al. Focal loss for dense object detection. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 2999-3007(2017).
[18] Liang X, Zhang J, Zhuo L et al. Small object detection in unmanned aerial vehicle images using feature fusion and scaling-based single shot detector with spatial context analysis[J]. IEEE Transactions on Circuits and Systems for Video Technology(2019).
[19] Xie S N, Girshick R, Dollar P et al. Aggregated residual transformations for deep neural networks. [C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA. New York: IEEE, 5987-5995(2017).
[20] Hu J, Shen L, Sun G. Squeeze-and-excitation networks. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 7132-7141(2018).
[21] Liu S, Qi L, Qin H F et al. Path aggregation network for instance segmentation. [C]∥2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 8759-8768(2018).
[26] Lin T Y, Maire M, Belongie S et al. Microsoft COCO: common objects in context[M]. ∥Fleet D, Pajdla T, Schiele B, et al. Computer vision-ECCV 2014. Lecture notes in computer science. Cham: Springer, 8693, 740-755(2014).
[27] Bodla N, Singh B, Chellappa R et al. Soft-NMS: improving object detection with one line of code. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 5562-5570(2017).