Electronics Optics & Control, Volume. 30, Issue 2, 24(2023)

A Lightweight Object Detection Algorithm Based on Improved YOLOv5s

YANG Jinhui1...2,3, LI Hong1,2,3, DU Yunyan1,2,3, MAO Yao1,2,3, and LIU Qiong1,23 |Show fewer author(s)
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    References(20)

    [1] [1] REDMON J, DIVVALA S, GIRSHICK R, et al.You only look once:unified, real-time object detection[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition.Las Vegas, NV:IEEE, 2016:779-788.

    [2] [2] REDMON J, FARHADI A.YOLO9000:better, faster, stronger[C]//Proceedings of the 2017 IEEE Conference on Compu-ter Vision and Pattern Recognition.Honolulu, HI:IEEE, 2017: 6517-6525.

    [3] [3] REDMON J, FARHADI A.YOLOv3:an incremental improvement[EB/OL].[2021-04-08].https://arxiv.org/pdf/1804. 02767.pdf.

    [4] [4] BOCHKOVSKIY A, WANG C Y, LIAO H Y M.YOLOv4:optimal speed and accuracy of object detection[EB/OL].[2020-05-09].https://arxiv.org/abs/2004.10934v1.

    [5] [5] GIRSHICK R, DONAHUE J, DARRELL T, et al.Rich feature hierarchies for accurate object detection and semantic segmentation[C]//Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition.Columbus, OH:IEEE, 2014:580-587.

    [6] [6] GIRSHICK R.Fast R-CNN[C]//Proceedings of the 2015 IEEE International Conference on Computer Vision.Washington, D.C.:IEEE, 2015:1440-1448.

    [7] [7] REN S Q, HE K M, GIRSHICK R, et al.Faster R-CNN:towards real-time object detection with region proposal networks[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6):1137-1149.

    [8] [8] KONG T, YAO A B, CHEN Y R, et al.HyperNet:towards accurate region proposal generation and joint object detection[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition.Las Vegas, NV:IEEE, 2016:845-853.

    [9] [9] CHO M A, CHUNG T Y, LEE H M, et al.N-RPN:hard example learning for region proposal networks[C]//IEEE International Conference on Image Processing(ICIP).Taipei:IEEE, 2019:3955-3959.

    [10] [10] RAO Y B, CHENG Y M, XUE J M, et al.FPSiamRPN:feature pyramid Siamese network with region proposal network for target tracking[J].IEEE Access, 2020, 8:176158-176169.

    [11] [11] ZHONG Q Y, LI C, ZHANG Y Y, et al.Cascade region proposal and global context for deep object detection[J].Neurocomputing, 2020, 395:170-177.

    [12] [12] CAI C L, CHEN L, ZHANG X Y, et al.End-to-end optimized ROI image compression[J].IEEE Transactions on Image Processing, 2020, 29:3442-3457.

    [13] [13] SEFERBEKOV S, IGLOVIKOV V, BUSLAEV A, et al.Feature pyramid network for multi-class land segmentation[C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops(CVPRW).Salt Lake City, UT:IEEE, 2018:272-275.

    [14] [14] HOWARD A, SANDLER M, CHEN B, et al.Searching for MobileNetV3[C]//International Conference on Computer Vision(ICCV).Seoul:IEEE, 2019:1314-1324.

    [15] [15] XIONG S Q, WU X H, CHEN H G, et al.Bi-directional skip connection feature pyramid network and sub-pixel convolution for high-quality object detection[J].Neurocomputing, 2021, 440:185-196.

    [16] [16] WANG C Y, LIAO H Y M, WU Y H, et al.CSPNet:a new backbone that can enhance learning capability of CNN[C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops(CVPRW).Seattle, WA:IEEE, 2020:1571-1580.

    [17] [17] HE K M, ZHANG X Y, REN S Q, et al.Spatial pyramid pooling in deep convolutional networks for visual recognition[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015, 37(9):1904-1916.

    [18] [18] LIU S, QI L, QIN H F, et al.Path aggregation network for instance segmentation[C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition.Salt Lake City, UT:IEEE, 2018:8759-8768.

    [19] [19] LIN T Y, DOLLR P, GIRSHICK R, et al.Feature pyramid networks for object detection[C]//Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition.Honolulu, HI:IEEE, 2017:936-944.

    [21] [21] HAN K, WANG Y H, TIAN Q, et al.GhostNet:more features from cheap operations[C]//Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition.Seattle, WA:IEEE, 2020:1577-1586.

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    YANG Jinhui, LI Hong, DU Yunyan, MAO Yao, LIU Qiong. A Lightweight Object Detection Algorithm Based on Improved YOLOv5s[J]. Electronics Optics & Control, 2023, 30(2): 24

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    Paper Information

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    Received: Dec. 21, 2021

    Accepted: --

    Published Online: Apr. 3, 2023

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2023.02.005

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