Cargando…
Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops
In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We...
Autores principales: | de Castro, Ana-Isabel, Jurado-Expósito, Montserrat, Gómez-Casero, María-Teresa, López-Granados, Francisca |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Scientific World Journal
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3354564/ https://www.ncbi.nlm.nih.gov/pubmed/22629171 http://dx.doi.org/10.1100/2012/630390 |
Ejemplares similares
-
Evaluating RGB Imaging and Multispectral Active and Hyperspectral Passive Sensing for Assessing Early Plant Vigor in Winter Wheat
por: Prey, Lukas, et al.
Publicado: (2018) -
Applying a weed risk assessment approach to GM crops
por: Keese, Paul K., et al.
Publicado: (2013) -
Discriminating Crop, Weeds and Soil Surface with a Terrestrial LIDAR Sensor
por: Andújar, Dionisio, et al.
Publicado: (2013) -
Crop/Weed Discrimination Using a Field Imaging Spectrometer System
por: Liu, Bo, et al.
Publicado: (2019) -
Identification of Weeds Based on Hyperspectral Imaging and Machine Learning
por: Li, Yanjie, et al.
Publicado: (2021)