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  • 标题:Pine wilt disease spreading prevention system using semantic segmentation
  • 本地全文:下载
  • 作者:Chulhyun Hwang ; Jaean Jeong ; Hoekyung Jung
  • 期刊名称:International Journal of Electrical and Computer Engineering
  • 电子版ISSN:2088-8708
  • 出版年度:2021
  • 卷号:11
  • 期号:3
  • 页码:2666
  • DOI:10.11591/ijece.v11i3.pp2666-2673
  • 出版社:Institute of Advanced Engineering and Science (IAES)
  • 摘要:Pine wilt disease is a disease that affects ecosystems by rapidly killing trees in a short period of time due to the close interaction between three factors such as trees, mediates, and pathogens. There is no 100% mortality infectious forest pests. According to the Korea Forest Service survey, as of April 2019, the damage of pine re-nematode disease was about 490,000 dead trees in 117 cities, counties and wards across the country. It's a fatal condition. In order to prevent this problem, this paper proposes a system that detects dead trees, early infection trees, and the like, using deep learning-based semantic segmentation. In addition, drones were used to photograph the area of the forest, and a separate pixel segmentation label could be used to identify three levels of transmission information: Suspicion, attention, and confirmation. This allows the user to grasp information such as area, location, and alarm to prevent the spread of re-nematode disease.
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