[1] Xiaofeng Zhao, Yebin Xu, Fei Wu, . Ground infrared target detection method based on a parallel attention mechanism (Invited). Infrared and Laser Engineering, 51, 20210290(2022).

[2] Peng Tang, Yi Liu, Hongguang Wei, . Automatic recognition algorithm of digital instrument reading in offshore booster station based on Mask-RCNN. Infrared and Laser Engineering, 50, 20211057(2021).

[3] Ming Chen, Lianfei Zhao, Limin Yuan, . Insulator detection method based on feature selection YOLOv3network. Infrared and Laser Engineering, 49, 20200401(2020).

[4] F Xie, M Dong, X Wang, et al. Infrared small-target detection using multiscale local average gray difference measure. Electronics, 11, 1547(2022).

[5] W Mo, J Pei. Nighttime infrared ship target detection based on two-channel image separation combined with saliency mapping of local grayscale dynamic range. Infrared Physics & Technology, 127, 104416(2022).

[6] L Li, G Liu, Z Li, et al. Infrared ship detection based on time fluctuation feature and space structure feature in sun-glint scene. Infrared Physics & Technology, 115, 103693(2021).

[7] [7] Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies f accurate object detection semantic segmentation[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2014: 580−587.

[8] S Ren, K He, R Girshick, et al. Faster R-CNN: Towards real-time object detection with region proposal networks. Advances in Neural Information Processing Systems, 39, 1137-1149(2015).

[9] [9] Liu W, Anguelov D, Erhan D, et al. SSD: Single shot multibox detect[C]European Conference on Computer Vision. Springer, Cham, 2016: 21−37.

[10] [10] Lin T Y, Goyal P, Girshick R, et al. Focal loss f dense object detection [C]Proceedings of IEEE International Conference on Computer Vision, 2017: 2980−2988.

[11] [11] Redmon J, Farhadi A. Yolov3: An incremental improvement[EBOL]. (20180408)[20230105]. https:arxiv.gabs180402767.

[12] [12] Bochkovskiy A, Wang C, Liao H. YOLOv4: Optimal speed accuracy of object detection [EBOL]. (20200423)[20230105]. https:arxiv.gabs2004. 10934.

[13] J Ye, Z Yuan, C Qian, et al. CAA-YOLO: Combined-attention-augmented YOLO for infrared ocean ships detection. Sensors, 22, 3782(2022).

[14] L Li, L Jiang, J Zhang, et al. A complete YOLO-based ship detection method for thermal infrared remote sensing images under complex backgrounds. Remote Sensing, 14, 1534(2022).

[15] [15] Miao L, Li N, Zhou M, et al. CBAMYolov5: improved Yolov5 based on attention model f infrared ship detection[C]International Conference on Computer Graphics, Artificial Intelligence, Data Processing, SPIE, 2022, 12168: 564−571.

[16] Wenjie Wang, Xiaohai He, Linbo Qing, . Improved YOLOv5 ship detection algorithm and embedded implemen-tation. Radio Engineering, 52, 2116-2123(2022).

[17] [17] Zhou D, Fang J, Song X, et al. Iou loss f 2D3D object detection[C]International Conference on 3D Vision, 2019: 8594.

[18] Z Zheng, P Wang, D Ren, et al. Enhancing geometric factors in model learning and inference for object detection and instance segmentation. IEEE Transactions on Cybernetics, 52, 8574-8586(2021).

[19] [19] Rezatofighi H, Tsoi N, Gwak J, et al. Generalized intersection over union: a metric a loss f bounding box regression[C]2019 IEEECVF Conference on Computer Vision Pattern Recognition, 2019: 658666.

[20] [20] Zheng Z, Wang P, Liu W, et al. DistanceIoU loss: faster better learning f bounding box regression[C]Proceedings of the Association f the Advance of Artificial Intelligence Conference on Artificial Intelligence, 2020: 1299313000.