Detecting infrared UAVs on edge devices through lightweight instance segmentation.

Journal: PloS one
Published Date: Aug 18, 2025

Abstract

MOTIVATION: Infrared unmanned aerial vehicle (UAV) detection for surveillance applications faces three conflicting requirements: accurate detection of pixel-level thermal signatures, real-time processing capabilities, and deployment feasibility on resource-constrained edge devices. Current deep learning approaches typically optimize for one or two of these objectives while compromising the third.

Authors

  • YuZhi Chen
    Hebei University of Architecture, Zhangjiakou, China.
  • Haoyue Sun
    College of Information Engineering, Hebei University of Architecture, Zhangjiakou, China.
  • Liang Tian
  • Ye Yang
    Department of Rehabilitation Medicine, Guilin People's Hospital, Guilin, Guangxi Zhuang Autonomous Region, China.
  • ShenYang Wang
    Hebei University of Architecture, Zhangjiakou, China.
  • Tianyou Wang
    College of Polymer Science and Engineering, State Key Laboratory of Advanced Polymer Materials, Sichuan University, Chengdu 610065, China.

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