[1] Xuening WANG, Junhui LI, Yuan ZHAI. Analysis on the development environment of intelligent automobile industry in China. Auto Industry Research, 8-10(2023).

[2] [2] 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.

[3] [3] GIRSHICK R. Fast RCNN [C]Proceedings of the IEEE International Conference on Computer Vision, IEEE, 2015: 14401448.

[4] [4] REN S, HE K, GIRSHICK R, et al. Faster RCNN: Towards realtime object detection with region proposal wks [J]. Advances in Neural Infmation Processing Systems , 2017, 39(6): 11371149.

[5] [5] HE K, GKIOXARI G, DOLLÁR P, et al. Mask RCNN [C]Proceedings of the IEEE International Conference on Computer Vision, 2017: 29612969.

[6] [6] LIU W, ANGUELOV D, ERHAN D, et al. SSD: Single shot multibox detect [C]Computer VisionECCV 2016, 2016, 9905: 2137.

[7] [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] [8] REDMON J, FARHADI A. YOLO9000: Better, faster, stronger [C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2017: 72637271.

[9] [9] REDMON J, FARHADI A. YOLOv3: An incremental improvement [DBOL]. (20180408) [20240914]. https:arxiv.gabs1804.02767.

[10] [10] BOCHKOVSKIY A, WANG C Y, LIAO H Y M. YOLOv4: Optimal speed accuracy of object detection [DBOL]. (20200423) [20240914]. https:arxiv.gabs2004.10934.

[11] [11] ZHU X, LYU S, WANG X, et al. TPHYOLOv5: Improved YOLOv5 based on transfmer prediction head f object detection on dronecaptured scenarios [C]Proceedings of the IEEECVF International Conference on Computer Vision, 2021: 27782788.

[12] [12] LI C, LI L, JIANG H, et al. YOLOv6: A singlestage object detection framewk f industrial applications [DBOL]. (20180408) [20240914]. https:arxiv.gabs1804.02767.

[13] [13] WANG C Y, BOCHKOVSKIY A, LIAO H Y M. YOLOv7: Trainable bagoffreebies sets new stateoftheart f realtime object detects [C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2023: 74647475.

[14] S LI, Y LI, Y LI, Al ET. YOLO-Firi: Improved YOLOv5 for infrared image object detection. IEEE Access, 9, 141861-141875(2021).

[15] Y CHEN, H SHIN. Pedestrian detection at night in infrared images using an attention-guided encoder-decoder convolutional neural network. Applied Sciences, 10, 809(2020).

[16] L ZHOU, S GAO, S WANG et al. IPD-net: infrared pedestrian detection network via adaptive feature extraction and coordinate information fusion. Sensors, 22, 8966(2022).

[17] X ZHAO, Y XIA, W ZHANG et al. YOLO-ViT-based method for unmanned aerial vehicle infrared vehicle target detection. Remote Sensing, 15, 3778(2023).

[18] [18] LIU S, QI L, QIN H, et al. Path aggregation wk f instance segmentation [C]Proceedings of the 2018 IEEECVF Conference on Computer Vision Pattern Recognition, 2018: 87598768.

[19] [19] SUNKARA R, LUO T. No me strided convolutions pooling: A new CNN building block f lowresolution images small objects [C]Joint European Conference on Machine Learning Knowledge Discovery in Databases. Cham: Springer Nature Switzerl, 2022: 443459.

[20] [20] JIE HU, LI SHEN, GANG SUN. Squeezeexcitation wks [C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2018: 71327141.

[21] [21] SZEGEDY C, VANHOUCKE V, IOFFE S, et al. Rethinking the inception architecture f computer vision [C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition, 2016: 28182826.

[22] Y F ZHANG, W REN, Z ZHANG et al. Focal and efficient IOU loss for accurate bounding box regression. Neurocomputing, 506, 146-157(2022).

[23] [23] WOO S, PARK J, LEE J Y, et al. CBAM: Convolutional block attention module [C]Proceedings of the European Conference on Computer Vision (ECCV), 2018: 319.

[24] [24] HOU Q, ZHOU D, FENG J. Codinate attention f efficient mobile wk design [C]Proceedings of the IEEECVF Conference on Computer Vision Pattern Recognition, 2021: 1371313722.

[25] [25] OUYANG D, HE S, ZHANG G, et al. Efficient multiscale attention module with crossspatial learning [C]ICASSP 20232023 IEEE International Conference on Acoustics, Speech Signal Processing (ICASSP), IEEE, 2023: 15.