Genetic algorithm based new sequence of principal component regression (GA-NSPCR) for feature selection and yield prediction using hyperspectral remote sensing data.
Sidik MulyonoMohamad Ivan FananyTjan BasaruddinPublished in: IGARSS (2012)
Keyphrases
- remote sensing data
- hyperspectral
- remote sensing
- feature selection
- multispectral
- principal component regression
- hyperspectral images
- infrared
- remote sensing images
- remote sensing imagery
- target detection
- land cover classification
- hyperspectral imagery
- hyperspectral data
- remotely sensed
- satellite images
- spatial resolution
- image data
- neural network
- prediction model
- change detection
- model selection
- information content
- high resolution
- image analysis
- partial least squares
- land cover
- feature set
- machine learning
- multispectral images
- mutual information
- dimensionality reduction
- support vector
- principal components
- classification accuracy
- feature extraction
- image segmentation
- image processing