Semantic Segmentation Based Field Detection Using Drones

Keita Endo, Tomotaka Kimura, Nobuhiko Itoh, T. Hiraguri
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引用次数: 2

Abstract

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.
基于语义分割的无人机现场检测
智能农业因其能提高工作效率而备受关注。例如,无人机和人工智能(AI)等先进技术可能会减少劳动力,提高生产率,并种植出高质量的作物。我们的研究目的是使用无人机从空中拍摄大葱的田地,然后使用AI图像分析来预测收获时间和观察生长情况。因此,在本文中,我们提出了基于深度学习的分割方法对各个田的种植情况进行区域截面分类的基本技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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