The doi 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: 10.4121/13173422

Afonso, Manya; Fonteijn, Hubert; Polder, G. (Gerrit); Wehrens, Ron; Lensink, Dick et. al. (2021): Rob2Pheno Annotated Tomato Image Dataset. Version 3. 4TU.ResearchData. dataset. https://doi.org/10.4121/13173422.v3

Dataset

x choose version: version 2 - 2021-02-26 version 1 - 2021-02-25

• Horticultural Crops

computer vision in agriculture, deep learning, greenhouse, phenotyping, tomato

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Manya Afonso , Hubert Fonteijn, G. (Gerrit) Polder , Ron Wehrens, Dick Lensink, Nanne Faber, Marcel Mooij

Dataset of RGBD images of tomato plants in a production greenhouse (Enza Zaden BV) obtained using Realsense cameras, and object instance level ground truth annotations of the fruit for using object detectors such as MaskRCNN or YOLACT. These data were used to obtain the results reported in our paper Tomato Fruit Detection and Counting in Greenhouses using Deep Learning, Frontiers in Plant Science, 2020.

• 2021-02-25 first online

• 2021-03-01 published, posted

4TU.ResearchData

Tomato Fruit Detection and Counting in Greenhouses using Deep Learning

• Foundation TKI Horticulture & Propagation Materials

Mathematical & Statistical Methods, Wageningen University & Research
ENZA Zaden