Detection of tipburn of lettuce produced at plant factory with artificial light using Convolutional Neural Networks

カテゴリ: 部門大会

論文No: SS1-2

グループ名: 【C】2021年電気学会電子・情報・システム部門大会

発行日: 2021/09/08

タイトル(英語): Detection of tipburn of lettuce produced at plant factory with artificial light using Convolutional Neural Networks

著者名: 森 貴哉（千葉大学）,中間 公啓（千葉大学）,小圷 成一（千葉大学）

著者名(英語): Takaya Mori (Chiba University),Kimihiro Nakama (Chiba University),Seiichi Koakutsu (Chiba University)

キーワード: 植物工場|チップバーン|機械学習|畳み込みニューラルネットワーク|Raspberry PiF値|Plant Factory|Tipburn|Machine Learning|Convolutional Neural Networks|Raspberry PiF-number

要約(日本語): In recent years, plant factory technology has attracted attention as a technology for stably producing plants. In many cases, leafy vegetables are grown in artificial light-type plant factories. In particular, lettuce has become a major crop. However, lettuce and other leafy vegetables suffer from a physiological disorder called tipburn. Therefore, Convolutional Neural Network is used to automatically identify the tipburn. In this study, we aim to implement the tipburn detection of lettuce produced in an artificial light plant factory on a small Raspberry Pi. However, images for training have different F-numbers than small cameras. As a result of experiments, it was confirmed that the number of images is more important for image classification than the difference in F-number of images.

PDFファイルサイズ: 418 Kバイト