Cargando…
From Prototype to Inference: A Pipeline to Apply Deep Learning in Sorghum Panicle Detection
Head (panicle) density is a major component in understanding crop yield, especially in crops that produce variable numbers of tillers such as sorghum and wheat. Use of panicle density both in plant breeding and in the agronomy scouting of commercial crops typically relies on manual counts observatio...
Autores principales: | James, Chrisbin, Gu, Yanyang, Potgieter, Andries, David, Etienne, Madec, Simon, Guo, Wei, Baret, Frédéric, Eriksson, Anders, Chapman, Scott |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AAAS
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076054/ https://www.ncbi.nlm.nih.gov/pubmed/37040294 http://dx.doi.org/10.34133/plantphenomics.0017 |
Ejemplares similares
-
Sorghum Panicle Detection and Counting Using Unmanned Aerial System Images and Deep Learning
por: Lin, Zhe, et al.
Publicado: (2020) -
A Weakly Supervised Deep Learning Framework for Sorghum Head Detection and Counting
por: Ghosal, Sambuddha, et al.
Publicado: (2019) -
VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation
por: Madec, Simon, et al.
Publicado: (2023) -
Genome-Wide Association Mapping Identifies Novel Panicle Morphology Loci and Candidate Genes in Sorghum
por: Wang, Lihua, et al.
Publicado: (2021) -
Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery
por: Zhao, Yan, et al.
Publicado: (2021)