Deep Learning Based Route Information Extraction from Satellite Imagery for Agricultural Machinery Management

被引:1
|
作者
Chien, Yu-Cheng [1 ]
Yeh, Yi-Chun [2 ]
Huang, Nen-Fu [2 ]
机构
[1] Natl Tsing Hua Univ, Inst Commun Engn, Hsinchu, Taiwan
[2] Natl Tsing Hua Univ, Dept Comp Sci, Hsinchu, Taiwan
关键词
Agricultural Machinery; Satellite Imagery Analysis; Image Segmentation; CV Processing; Management System;
D O I
10.1109/ICOIN53446.2022.9687152
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
More and more agricultural machinery has been used to pursue efficiency, automation, and precision in agriculture. To manage their agricultural machinery, farmers must know the position of the machinery. Therefore, we propose Management System, including GPS sensors, API Server and Web Server, to realize that. Moreover, the arrangement of the farm, such as the distribution of routes and districts, is equally important. We introduce Extraction Server, composed of a designed image segmentation model and CV post-processing, for the acquirement of the arrangement of farms. Finally, the conducted experiments show that Extraction Server can yield the arrangement of farms. We plan two different scenarios to validate Management System. It is proven to be helpful to analyze the operation of machines.
引用
收藏
页码:101 / 106
页数:6
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