Laser & Optoelectronics Progress, Volume. 59, Issue 4, 0415002(2022)

Improved YOLOv3 Garbage Classification and Detection Model for Edge Computing Devices

Zipeng Wang, Rongfen Zhang*, Yuhong Liu, Jihui Huang, and Zhixu Chen
Author Affiliations
  • College of Big Data and Information Engineering, Guizhou University, Guiyang , Guizhou 550025, China
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    References(23)

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    [5] Ning K, Zhang D B, Yin F et al. Garbage detection and classification of intelligent sweeping robot based on visual perception[J]. Journal of Image and Graphics, 24, 1358-1368(2019).

    [17] Li C Y, Yao J M, Lin Z X et al. Object detection method based on improved YOLO lightweight network[J]. Laser & Optoelectronics Progress, 57, 141003(2020).

    [18] Cui J H, Zhang Y Z, Wang Z et al. Light-weight object detection networks for embedded platform[J]. Acta Optica Sinica, 39, 0415006(2019).

    [19] Chen L L, Zhang Z D, Peng L. Real-time detection based on improved single shot MultiBox detector[J]. Laser & Optoelectronics Progress, 56, 011002(2019).

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    Zipeng Wang, Rongfen Zhang, Yuhong Liu, Jihui Huang, Zhixu Chen. Improved YOLOv3 Garbage Classification and Detection Model for Edge Computing Devices[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0415002

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    Paper Information

    Category: Machine Vision

    Received: Feb. 5, 2021

    Accepted: Mar. 25, 2021

    Published Online: Jan. 25, 2022

    The Author Email: Zhang Rongfen (rfzhang@gzu.edu.cn)

    DOI:10.3788/LOP202259.0415002

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