RoseTracker: A system for automated rose growth monitoring

Shinoda Risa; 篠田 理沙; Motoki Ko; 元木 航; Hara Kensho; Kataoka Hirokatsu; Nakano Ryohei; 中野 龍平; Nakazaki Tetsuya; 中﨑 鉄也; Noguchi Ryozo; 野口 良造

タイトル	en RoseTracker: A system for automated rose growth monitoring
作成者	en Shinoda, Risa ja 篠田, 理沙 en Motoki, Ko ja 元木, 航 en Hara, Kensho en Kataoka, Hirokatsu en Nakano, Ryohei ja 中野, 龍平 e-Rad_Researcher 70294444 ROR https://ror.org/02kpeqv85 en Nakazaki, Tetsuya ja 中﨑, 鉄也 en Noguchi, Ryozo ja 野口, 良造 e-Rad_Researcher 60261773 ROR https://ror.org/02kpeqv85
アクセス権	open access
権利情報	en © 2023 The Author(s). Published by Elsevier B.V. http://creativecommons.org/licenses/by/4.0/ en This is an open access article under the CC BY license.
主題	Other en Rose Other en Deep learning Other en Object detection Other en Tracking Other en Dataset
内容注記	Abstract en In cut-flower cultivation, production planning is an important task because demand fluctuates throughout the year. For precise cultivation planning, understanding the cultivation status is necessary by the growing stage. However, manually counting all the roses in the greenhouse to determine the cultivation status is difficult without incurring considerable time and labor. Some studies have engaged in detecting the number of flowers, but these studies used close-up images and could not count flowers without omissions or overlapping in an entire farm. In addition, limited datasets for object detection based on cut-flower blooming stages are available. In this study, we propose the RoseBlooming dataset and an efficient rose-monitoring system called RoseTracker to bridge the gap between computer vision techniques and the horticulture cultivation industry. The RoseBlooming dataset is the innovative dataset of labeled images for cut flowers at the growing stage. RoseTracker can detect small roses from various angles while moving the camera, reduces detection omissions, and achieves an F1 score of 0.950, thereby outperforming conventional models. For application, we used overhead images captured under actual growing conditions. RoseTracker and the RoseBlooming dataset contribute to constructing the rose-growth monitoring system in high demand worldwide.
出版者	en Elsevier BV
日付	Issued2023-10
言語	eng
資源タイプ	journal article
出版タイプ	VoR
資源識別子	HDL http://hdl.handle.net/2433/284496
関連	isIdenticalTo DOI https://doi.org/10.1016/j.atech.2023.100271
収録誌情報	EISSN 2772-3755 en Smart Agricultural Technology 巻5
ファイル	fulltext j.atech.2023.100271.pdf (application/pdf)
コンテンツ更新日時	2026-02-18