Hybrid-YOLOv5 for object detection of non-ferrous metals in end-of-life vehicles.

Journal: Scientific reports
Published Date: Jul 2, 2025

Abstract

In recent years, the detection of non-ferrous metals in end-of-life vehicles (ELVs) has become essential for improving recycling in the circular economy. Traditional methods struggle with accurate detection due to the variety of metals and challenging industrial environments. This study proposes a Hybrid-YOLOv5-based algorithm for efficiently detecting copper, aluminum, and stainless steel in ELVs. The goal is to enhance detection accuracy and computational efficiency in metal sorting. By integrating the Coarse-to-Fine (C2F) module, Squeeze-and-Excitation (SE) module, and MobileNetV3 backbone, we significantly improve performance and speed. On a dataset of 2,500 infrared images, Hybrid-YOLOv5 achieves 84.2% mAP@0.5 and 60 FPS inference speed, outperforming YOLOv3, YOLOv5, YOLOv7, and YOLOv11 by 22.2%, 12.4%, 11.1%, and 36.2% in mAP@0.5, respectively. This work provides an efficient solution for industrial metal sorting and intelligent recycling in the circular economy.

Authors

  • Youdong Jia
    Faculty of Mechanical and Electrical Engineering, Kunming University, Kunming, 650214, People's Republic of China.
  • YuHang Zhang
    Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. Electronic address: yhzhang@sibs.ac.cn.
  • Rui Yang
    Department of Biomedical Informatics, Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.
  • Xinzhi Li
    Hubei Key Laboratory of Tumor Microenvironment and Immunotherapy, Three Gorges University, Yichang, 443002, Hubei, China. lixpj@163.com.
  • Zhengfang Li
    Department of Rheumatology and Immunology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China.
  • Sibo Yao
    School of Mechanical Engineering & Automation, Northeastern University, Shenyang, 110819, People's Republic of China.
  • Jiaxing Zeng
    Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming, 650500, People's Republic of China.
  • Ziyue Zhu
    The Department of Bioengineering, Imperial College London, SW7 2AZ London, UK.
  • Yuanxin Zhang
    Faculty of Mechanical and Electrical Engineering, Kunming University, Kunming, 650214, People's Republic of China.

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