Cargando…
ROSE-X: an annotated data set for evaluation of 3D plant organ segmentation methods
BACKGROUND: The production and availability of annotated data sets are indispensable for training and evaluation of automatic phenotyping methods. The need for complete 3D models of real plants with organ-level labeling is even more pronounced due to the advances in 3D vision-based phenotyping techn...
Autores principales: | Dutagaci, Helin, Rasti, Pejman, Galopin, Gilles, Rousseau, David |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057657/ https://www.ncbi.nlm.nih.gov/pubmed/32158494 http://dx.doi.org/10.1186/s13007-020-00573-w |
Ejemplares similares
-
Segmentation of structural parts of rosebush plants with 3D point-based deep learning methods
por: Turgut, Kaya, et al.
Publicado: (2022) -
Toward Joint Acquisition-Annotation of Images with Egocentric Devices for a Lower-Cost Machine Learning Application to Apple Detection
por: Samiei, Salma, et al.
Publicado: (2020) -
Machine Learning-Based Classification of Powdery Mildew Severity on Melon Leaves
por: El Abidine, Mouad Zine, et al.
Publicado: (2020) -
The annotation and analysis of complex 3D plant organs using 3DCoordX
por: Vijayan, Athul, et al.
Publicado: (2022) -
Enhancing the Tracking of Seedling Growth Using RGB-Depth Fusion and Deep Learning
por: Garbouge, Hadhami, et al.
Publicado: (2021)