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Exotic Weed Image Recognition System Based on ResNeXt Model

ResNeXt 모델 기반의 외래잡초 영상 판별 시스템

  • Kim, Min-Soo (Dept. of Electronics Convergence Eng., Kwangwoon University) ;
  • Lee, Gi Yong (Dept. of Electronics Convergence Eng., Kwangwoon University) ;
  • Kim, Hyoung-Gook (Dept. of Electronics Convergence Eng., Kwangwoon University)
  • Received : 2021.04.06
  • Accepted : 2021.06.09
  • Published : 2021.06.30

Abstract

In this paper, we propose a system that recognizes weed images using a classifier based on ResNeXt model. On the server of the proposed system, the ResNeXt model extracts the fine features of the weed images sent from the user and classifies it as one of the most similar weeds out of 21 species. And the classification result is delivered to the client and displayed on the smartphone screen through the application. The experimental results show that the proposed weed recognition system based on ResNeXt model is superior to existing methods and can be effectively applied in the real-world agriculture field.

Keywords

References

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