Remote Sensing and Machine Learning Modeling to Support the Identification of Sugarcane Crops.
Carlos Andres Lozano-GarzonGermán Enrique Bravo CórdobaHarold CastroGeovanny González-RodríguezDavid NiñoHaydemar NúñezCarolina PardoAurelio VivasYuber CastroJazmin MedinaLuis Carlos MottaJulio Rene RojasLuis Ignacio SuárezPublished in: IEEE Access (2022)
Keyphrases
- remote sensing
- machine learning
- hyperspectral
- change detection
- remote sensing images
- satellite images
- multispectral
- hyperspectral images
- remote sensing data
- remote sensing imagery
- high resolution
- image fusion
- satellite imagery
- image analysis
- image processing
- weather prediction
- medical imaging
- remotely sensed images
- automatic image registration
- digital image analysis
- satellite data
- high spatial resolution
- remotely sensed
- multi spectral images
- environmental sciences
- data mining
- high resolution satellite images
- data assimilation
- remote sensed images
- remotely sensed imagery
- high quality
- land cover classification
- pattern recognition
- remote sensing image processing