深層学習を用いた画像認識技術の医療分野・農業分野への応用

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2024/09/01

タイトル(英語): Application of Image Recognition Technology Using Deep Learning to the Medical and Agricultural Fields

著者名: 渡辺　寛望（山梨大学），小谷　信司（山梨大学）

著者名(英語): Hiromi Watanabe (University of Yamanashi), Shinji Kotani (University of Yamanashi)

キーワード: 深層学習，病変候補検出，被害果検出，カプセル内視鏡，サクランボ　　deep learning，lesion detection，anomaly detection，capsule endoscopy，cherry

要約(英語): Image recognition technology using deep learning is being actively researched every day, and the application fields of image recognition technology are expanding. For example, in the medical field, which many images are collected and diagnosed by humans, and in the agricultural field, which relies heavily on human experience. In this paper, the detection of lesion candidates in capsule endoscope images is described as an example of application of image recognition technology using deep learning to the medical field. And, as an example of application in the agricultural field, the anomaly detection in our automatic cherry sorting system is presented.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.144 No.9 （2024） 特集：知能メカトロニクス分野と連携する知覚情報技術

本誌掲載ページ: 864-867 p

原稿種別: 解説／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/144/9/144_864/_article/-char/ja/