[6] Redmon J, Farhadi A. YOLO9000: Better, Faster, Stronger[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017: 6517-6525.
[7] Bertinetto L, Valmadre J, Henriques J F, et al. Fully-convolutional siamese networks for object tracking[J/OL]. Computer Vision and Pattern Recognition, 2016. https://arxiv.org/abs/1606.09549
[15] RangiLyu. NanoDet-Plus: Super fast and high accuracy lightweight anchor-free object detection model[EB/OL]. https://github.com/ RangiLyu/nanodet, 2021.
[16] MA N, ZHANG X, ZHENG H T, et al. Shufflenet v2: Practical guidelines for efficient cnn architecture design[C]//Proceedings of the European Conference on Computer Vision (ECCV). 2018: 116-131.
[17] LI X, WANG W, WU L, et al. Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection[J]. Advances in Neural Information Processing Systems, 2020, 33: 21002-21012.
[18] JIANG Nan, WANG Kuiran, PENG Xiaoke. Anti-UAV: A Large-Scale Benchmark for Vision-Based UAV Tracking[J]. IEEE Transactions on Multimedia, 2023, 25: 486-500, DOI: 10.1109/TMM.2021.3128047.
[19] ZHAO J, WANG G, LI J, et al. The 2nd Anti-UAV workshop & challenge: Methods and results[J/OL]. arXiv preprint arXiv:2108.09909, 2021.
[20] LI C, LI L, JIANG H, et al. YOLOv6: A single-stage object detection framework for industrial applications[J/OL]. arXiv preprint arXiv:2209.02976, 2022.
[21] GE Z, LIU S, WANG F, et al. Yolox: Exceeding yolo series in 2021[J/OL]. arXiv preprint arXiv:2107.08430, 2021.
[22] Github. Yolov5[EB/OL]. https://github.com/ultralytics/yolov5, 2021.
[23] LI B, XIAO C, WANG L, et al. Dense nested attention network for infrared small target detection[J]. IEEE Transactions on Image Processing, 2022, 32: 1745-1758.
