Detection of the pine wilt disease using a joint deep object detection model based on drone remote sensing data

HIGHLIGHTS

• What: The experiments show that the average F1 reaches 0.92 and 0.90, respectively, and the counting accuracy is 0.91 and 0.90, respectively. In the fifth part, the experimental results are summarized, the shortcomings of the research are pointed out, and the future research direction is proposed. Considering the efficiency of data processing and the need to reduce information redundancy, this study proposed an OCP. This study proposed the intersection-to-union ratio method as the loss function, which is more effective than traditional mean square error and cross-entropy loss functions, as shown . . .
  

   

  

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