The doi above is for this specific version of this collection, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/f2ad72ce-3e5b-429e-ba14-78eed903ce03

Wen, Junhan; Camiel Verschoor; Thomas Abeel; de Weerdt, M.M. (Mathijs) (2025): Growth monitoring images of strawberries. Version 1. 4TU.ResearchData. collection. https://doi.org/10.4121/f2ad72ce-3e5b-429e-ba14-78eed903ce03.v1

Collection

• Artificial Intelligence and Image Processing
• Horticultural Production
• Other Information and Computing Sciences
• Agricultural and Veterinary Sciences
• Information and Computing Sciences

Biological Development, Computer Vision, Growth Monitoring, Horticulture Research, Long-term MOT, MOT Dataset, Multiple Object Tracking

2021.04.23-2024.06.27

by Junhan Wen , Camiel Verschoor, Thomas Abeel, M.M. (Mathijs) de Weerdt

The Growing Strawberries Dataset (GSD) is a curated multiple-object tracking (MOT) dataset designed to support the monitoring of strawberry growth. It consists of several subsets within the GSD family:

• GSD (the original dataset), collected and annotated in 2021 and 2022, which includes demonstration samples and MOT annotations.
• Extended-GSD, consisting of hourly daytime images collected in 2023 and 2024.
• Dark-GSD, which includes darker, nighttime images captured from 2021 to 2024 during the monitoring period.

These datasets provide comprehensive coverage for tracking strawberry growth under varying lighting and time conditions.

• 2025-01-23 first online, published, posted

4TU.ResearchData

The Growing Strawberries Dataset: Tracking Multiple Objects with Biological Development over an Extended Period

• Topsector Tuinbouw & Uitgangsmaterialen
• Innovatiefonds Hagelunie
• Interpolis

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Algorithmics group