The DOI displayed above is for this specific version of this dataset, 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: 10.4121/4250ca74-962a-4da6-a2bd-a763f0cea2a5

Wen, Junhan; Camiel Verschoor; Thomas Abeel; de Weerdt, M.M. (Mathijs) (2025): Dark Images of "The Growing Strawberries Dataset". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/4250ca74-962a-4da6-a2bd-a763f0cea2a5.v1

Categories

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

Keywords

Biological Development Computer Vision Dark MOT Dataset Growth Monitoring Horticulture Research Multiple-Object Tracking

Geolocation

Time coverage

2021.04.23-2024.06.27

Licence

CC BY-NC-ND 4.0

Collection

• Growth monitoring images of strawberries

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

This dataset contains the darker images extracted from The Growing Strawberries Dataset (GSD) and its extended version. GSD is a multiple-object tracking (MOT) dataset originally created to monitor the growth of strawberries. Across its various versions, GSD provides hourly images captured during cultivation periods spanning from 2021 to 2024. This particular dataset includes images that were excluded from GSD and extended-GSD (doi.org/10.4121/e3b31ece-cc88-4638-be10-8ccdd4c5f2f7), offering a unique subset for specialized analysis. Additionally, a small portion of images from 2021 and 2022, where strawberries are only faintly visible, are supplemented with MOT annotations.

History

• 2025-01-14 first online, published, posted

Publisher

4TU.ResearchData

Format

.jpg, .json

Associated peer-reviewed publication

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

Derived from

• https://doi.org/10.4121/e3b31ece-cc88-4638-be10-8ccdd4c5f2f7.v2

Funding

• Topsector Tuinbouw & Uitgangsmaterialen
• Innovatiefonds Hagelunie
• Interpolis

Organizations

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