Journal of Information Processing Systems

  • 제16권4호
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  • Pages.795-808
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  • 2020
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Aircraft Recognition from Remote Sensing Images Based on Machine Vision

  • Chen, Lu (Henan Key Laboratory of Big Data Analysis and Processing, Henan University) ;
  • Zhou, Liming (Henan Key Laboratory of Big Data Analysis and Processing, Henan University) ;
  • Liu, Jinming (School of Computer and Information Engineering, Henan University)
  • 투고 : 2020.02.26
  • 심사 : 2020.05.23
  • 발행 : 2020.08.31
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초록

Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introduced into the Yolov3 network structure, and then the data set was cluster analyzed using the k-means algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pre-training model and improved the resolution of the input image. Finally, our method adopted multi-scale training model. In this paper, we used remote sensing aircraft dataset of RSOD-Dataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.

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참고문헌

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