Semantic Segmentation Based Field Detection Using Drones

被引：1
|
作者：
Endo, Keita [1 ]
Kimura, Tomotaka [2 ]
Itoh, Nobuhiko [1 ]
Hiraguri, Takefumi [1 ]
机构：
[1] Nippon Inst Technol, Saitama, Japan
[2] Doshisha Univ, Kyotanabe, Kyoto, Japan
来源：
2022 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN, IEEE ICCE-TW 2022 | 2022年
关键词：
D O I：
10.1109/ICCE-TAIWAN55306.2022.9869088
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Smart agriculture has been garnering attention to improve the efficiency of works. For example, advanced technologies such as drones and Artificial Intelligence (AI) may reduce labor, increase productivity, and grow high-quality crops. The aim of our study is to photograph fields of green onions from the sky using drones, then to predict the harvest time and observe the growth situation using AI image analysis. Therefore, in this paper, we proposed basic technology for area section classification of each field by using segmentation method using deep learning to analyze the cultivation situation of each field.
引用
收藏
页码：213 / 214
页数：2
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