Cargando…
Pheno4D: A spatio-temporal dataset of maize and tomato plant point clouds for phenotyping and advanced plant analysis
Understanding the growth and development of individual plants is of central importance in modern agriculture, crop breeding, and crop science. To this end, using 3D data for plant analysis has gained attention over the last years. High-resolution point clouds offer the potential to derive a variety...
Autores principales: | Schunck, David, Magistri, Federico, Rosu, Radu Alexandru, Cornelißen, André, Chebrolu, Nived, Paulus, Stefan, Léon, Jens, Behnke, Sven, Stachniss, Cyrill, Kuhlmann, Heiner, Klingbeil, Lasse |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372960/ https://www.ncbi.nlm.nih.gov/pubmed/34407122 http://dx.doi.org/10.1371/journal.pone.0256340 |
Ejemplares similares
-
Registration of spatio-temporal point clouds of plants for phenotyping
por: Chebrolu, Nived, et al.
Publicado: (2021) -
Surface feature based classification of plant organs from 3D laserscanned point clouds for plant phenotyping
por: Paulus, Stefan, et al.
Publicado: (2013) -
Accuracy Analysis of a Multi-View Stereo Approach for Phenotyping of Tomato Plants at the Organ Level
por: Rose, Johann Christian, et al.
Publicado: (2015) -
UAV-based individual plant detection and geometric parameter extraction in vineyards
por: Cantürk, Meltem, et al.
Publicado: (2023) -
Real-Time Single-Frequency GPS/MEMS-IMU Attitude Determination of Lightweight UAVs
por: Eling, Christian, et al.
Publicado: (2015)