Automatic Identification of Lettuce Tipburn in Plant Factory Using Convolutional Neural Networks

カテゴリ: 部門大会

論文No: SS3-2

グループ名: 【C】2019年電気学会電子・情報・システム部門大会プログラム

発行日: 2019/08/28

タイトル(英語): Automatic Identification of Lettuce Tipburn in Plant Factory Using Convolutional Neural Networks

著者名: 上原 賢太(千葉大学),畠中 芳樹(千葉大学),嶋村 茂治(千葉大学),小圷 成一(千葉大学)

著者名(英語): Kenta Uehara|Yoshiki Hatakenaka|Shigeharu Shimamura|Seiichi Koakutsu

キーワード: Convolutional neural network|Diagnostic imaging|Plant factory|Plant physiological disorder

要約(日本語): Nowadays, plant factories are attracting worldwide attention as a technology for stably producing crops. One of the problems of plant factory is tipburn, which is a physiological disorder of crops. If tipburn occurs, tipburn leaves are trimmed by hand, or that lettuce is removed from products. Identifying tipburn by eye observation and trimming tipburn leaves by hand requires much labor and cost. In this study, we aim to perform and compare discrimination of tipburn occurrence and tipburn non-occurrence in lettuce cultivated at plant factories using convolutional neural networks with both multiple models and optimization methods. As a result of the experiment, it is confirmed that discrimination can be performed with high accuracy.

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