Cargando…
Editorial: Convolutional neural networks and deep learning for crop improvement and production
Autores principales: | Yang, Wanneng, Egea, Gregorio, Ghamkhar, Kioumars |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9716429/ https://www.ncbi.nlm.nih.gov/pubmed/36466228 http://dx.doi.org/10.3389/fpls.2022.1079148 |
Ejemplares similares
-
Editorial: Spectroscopy for crop and product phenotyping
por: Kalendar, Ruslan, et al.
Publicado: (2022) -
Assessment of Mixed Sward Using Context Sensitive Convolutional Neural Networks
por: Bateman, Christopher J., et al.
Publicado: (2020) -
Prospects for Trifolium Improvement Through Germplasm Characterisation and Pre-breeding in New Zealand and Beyond
por: Egan, Lucy M., et al.
Publicado: (2021) -
Weed Detection in Perennial Ryegrass With Deep Learning Convolutional Neural Network
por: Yu, Jialin, et al.
Publicado: (2019) -
Editorial: Phenotyping; From Plant, to Data, to Impact and Highlights of the International Plant Phenotyping Symposium - IPPS 2018
por: Pommier, Cyril, et al.
Publicado: (2020)