Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops

@inproceedings{Castro2012ApplyingNN,
  title={Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops},
  author={Ana-Isabel de Castro and Montserrat Jurado-Exp{\'o}sito and Mar{\'i}a-Teresa G{\'o}mez-Casero and Francisca L{\'o}pez-Granados},
  booktitle={TheScientificWorldJournal},
  year={2012}
}
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 aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance… CONTINUE READING