[3] Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies f accurate object detection semantic segmentation[C]2014 IEEE Conference on Computer Vision Pattern Recognition (CVPR), 2014: 580587.
[4] Girshick R. Fast RCNN [C]2015 IEEE International Conference on Computer Vision (ICCV), 2015: 14401448.
[6] Liu W, Anguelov D, Erhan D, et al. SSD: Single shot multibox detect [C]Computer VisionECCV 2016, 2016, 9905: 2137.
[7] Redmon J, Divvala S, Girshick R, et al. You only look once: unified, realtime object detection [C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2016: 779788.
[8] Redmon J, Farhadi A. YOLO9000: better, faster, stronger [C]30th IEEE Conference on Computer Vision Pattern Recognition (CVPR 2017), 2017: 65176525.
[11] Y Bai, R Li, S Gou, et al. Cross-connected bidirectional pyramid network for infrared small-dim target detection. IEEE Geoscience and Remote Sensing Letters, 19, 7506405(2022).
[14] Long Y, Jin D, Wu Z, et al. Accurate identification of infrared ship in islshe background based on visual attention [C]2022 IEEE AsiaPacific Conference on Image Processing, Electronics Computers (IPEC), 2022: 800806.
[15] Z Xu, J Zhuang, Q Liu, et al. Benchmarking a large-scale FIR dataset for on-road pedestrian detection. Infrared Physics & Technology, 96, 199-208(2019).
[16] Karasawa T, Watanabe K, Ha Q, et al. Multispectral object detection f autonomous vehicles [C]Proceedings of The Thematic Wkshops of ACM Multimedia 2017 (Thematic Wkshops'' 17), 2017: 3543.
[17] Hu J, Shen L, Sun G, et al. Squeezeexcitation wks [C]2018 IEEECVF Conference on Computer Vision Pattern Recognition (CVPR), 2018: 71327141.
[18] Woo S, Park J, Lee JY, et al. CBAM: convolutional block attention module [C]Computer VisionECCV 2018, PT VII, 2018, 11211: 319.
[19] Hou Q, Zhou D, Feng J, et al. Codinate attention f efficient mobile wk design [C]2021 IEEECVF Conference on Computer Vision Pattern Recognition, CVPR 2021, 2021: 1370813717.