Infrared Technology, Volume. 47, Issue 6, 739(2025)

Infrared Small Target Detection Algorithm for Field Robots

Jinxin TONG1, Gang JIANG1、*, Kairui HUANG1, Qingping CHEN2, and Wengang XU2
Author Affiliations
  • 1School of Mechanical and Electrical Engineering, Chengdu University of Technology, Chengdu 610059, China
  • 2Science and Technology Management Department, Chengdu Lingchuan Special Industries Limited Company, Chengdu 610105, China
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    References(16)

    [1] [1] WANG C Y, Bochkovskiy A, LIAO H Y M. YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors[J]. arXiv preprint arXiv: 2207.02696, 2022.

    [2] [2] LIU W, Anguelov D, Erhan D, et al. Ssd: single shot multibox detector[C]//European Conference on Computer Vision, Springer, Cham, 2016: 21-37.

    [3] [3] TAN M, PANG R, LE Q V. Efficientdet: scalable and efficient object detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020: 10781-10790.

    [4] [4] CHEN G, WANG H, CHEN K, et al. A survey of the four pillars for small object detection: multiscale representation, contextual information, super-resolution, and region proposal[J].IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2022,52(1): 203-219.

    [6] [6] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[J]. arXiv preprint arXiv: 1409.1556, 2014.

    [8] [8] Redmon J, Farhadi A. Yolov3: an incremental improvement[J]. arXiv preprint arXiv: 1804.02767, 2018.

    [11] [11] Vaswani A, Shazeer N, Parmar N, et al. Attention is all you need[J].Advances in Neural Information Processing Systems, 2017,30: 5998-6008.

    [12] [12] YANG C, HUANG Z, WANG N. QueryDet: cascaded sparse query for accelerating high-resolution small object detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022: 13668-13677.

    [13] [13] XU C, WANG J, YANG W, et al. RFLA: Gaussian receptive field based label assignment for tiny object detection[J]. arXiv preprint arXiv: 2208.08738, 2022.

    [14] [14] MA N, ZHANG X, LIU M, et al. Activate or not: learning customized activation[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021: 8032-8042.

    [15] [15] Park H J, Choi Y J, Lee Y W, et al. ssFPN: Scale sequence (S^ 2) feature based feature pyramid network for object detection[J]. arXiv preprint arXiv: 2208.11533, 2022.

    [16] [16] Gevorgyan Z. SIoU loss: more powerful learning for bounding box regression[J]. arXiv preprint arXiv: 2205.12740, 2022.

    [17] [17] HUANG L, ZHOU Y, WANG T, et al. Delving into the estimation shift of batch normalization in a network[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022: 763-772.

    [18] [18] WU Y, HE K. Group normalization[C]//Proceedings of the European Conference on Computer Vision(ECCV). 2018: 3-19.

    [19] [19] 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.

    [20] [20] Bochkovskiy A, WANG C Y, LIAO H Y M. Yolov4: Optimal speed and accuracy of object detection[J]. arXiv preprint arXiv: 2004.10934, 2020.

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    TONG Jinxin, JIANG Gang, HUANG Kairui, CHEN Qingping, XU Wengang. Infrared Small Target Detection Algorithm for Field Robots[J]. Infrared Technology, 2025, 47(6): 739

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    Paper Information

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    Received: Dec. 6, 2022

    Accepted: Jul. 3, 2025

    Published Online: Jul. 3, 2025

    The Author Email: JIANG Gang (7361246@qq.com)

    DOI:

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