Deep-learning-ready RGB-Depth imaging dataset of early-growth plants.

DOI

Dataset composed of RGB, Depth, and Infrared images acquired while monitoring the growth of tomatoes, beans and rapeseed. 11 trials were conducted from 14-01-2022 to 13-12-2022.

Python, 3.7.15

Identifier
DOI https://doi.org/10.57745/AMFJTK
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.57745/AMFJTK
Provenance
Creator MERCIER Félix ORCID logo; COUASNET Geoffroy; EL GHAZIRI Angelina; BOUHLEL Nizar; SARNIGUET Alain; MARCHI MURIEL; BARRET Matthieu ORCID logo; ROUSSEAU David
Publisher Recherche Data Gouv
Contributor MERCIER Félix; COUASNET Geoffroy; SARNIGUET Alain; MARCHI Muriel; MAROLLEAU Brice; ARNAULT Gontran; Entrepôt-Catalogue Recherche Data Gouv
Publication Year 2024
Rights etalab 2.0; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/etalab-2.0.html
OpenAccess true
Contact MERCIER Félix (University of Angers)
Representation
Resource Type Dataset
Format application/zip; text/tab-separated-values; text/plain
Size 6411425160; 21804830698; 13344517568; 6173686008; 10399303964; 20006583500; 36537086168; 22766211483; 26103436650; 14059555861; 12710507626; 4243; 754; 18017825; 8775
Version 1.0
Discipline Agriculture, Forestry, Horticulture; Computer Science; Agricultural Sciences; Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences