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Camouflaged target detection based on multimodal image input pixel-level fusion
Regular Papers | Updated：2024-09-29

    • Camouflaged target detection based on multimodal image input pixel-level fusion

    • 基于多模态图像输入端像素级融合的伪装目标检测
    • “In the field of camouflaged target detection, a new technique called MIF-YOLOv5 has been developed. This method uses multimodal image fusion and a loss function optimized by K-Means++ clustering to enhance detection accuracy and robustness. The technique has achieved a detection accuracy of 96.5% and a recognition probability of 92.5%, setting a new standard in the industry.”
    • Frontiers of Information Technology & Electronic Engineering   Vol. 25, Issue 9, Pages: 1226-1239(2024)

    • DOI：10.1631/FITEE.2300503    

      CLC： TP391

    • Received：26 July 2023，

      Revised：2023-11-14，

      Published：2024-09

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  • Ruihui PENG, Jie LAI, Xueting YANG, et al. Camouflaged target detection based on multimodal image input pixel-level fusion[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(9): 1226-1239. DOI： 10.1631/FITEE.2300503.

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