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Towards Real Time Detection of Rice Weed in Uncontrolled Crop Conditions

통제되지 않는 농작물 조건에서 쌀 잡초의 실시간 검출에 관한 연구

  • Umraiz, Muhammad (Division of Electronics and Information Engineering, Jeonbuk National University) ;
  • Kim, Sang-cheol (Core research institute of intelligent robots)
  • Received : 2020.01.08
  • Accepted : 2020.02.17
  • Published : 2020.03.31

Abstract

Being a dense and complex task of precisely detecting the weeds in practical crop field environment, previous approaches lack in terms of speed of processing image frames with accuracy. Although much of the attention has been given to classify the plants diseases but detecting crop weed issue remained in limelight. Previous approaches report to use fast algorithms but inference time is not even closer to real time, making them impractical solutions to be used in uncontrolled conditions. Therefore, we propose a detection model for the complex rice weed detection task. Experimental results show that inference time in our approach is reduced with a significant margin in weed detection task, making it practically deployable application in real conditions. The samples are collected at two different growth stages of rice and annotated manually

Acknowledgement

Supported by : National Research Foundation of Korea (NRF)

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