Sparsity-regularized feature selection for multi-class remote sensing image classification.
Tao ChenYe ZhaoYanrong GuoPublished in: Neural Comput. Appl. (2020)
Keyphrases
- multi class
- remote sensing
- image classification
- feature selection
- remotely sensed data
- sparse representation
- feature extraction
- multispectral
- change detection
- support vector machine
- remote sensing images
- image processing
- high resolution
- hyperspectral
- image analysis
- satellite data
- text categorization
- binary classification
- image features
- remote sensing data
- mutual information
- bag of words
- high dimensional
- land cover
- image representation
- multi task
- cost sensitive
- multi label
- multi class classification
- text classification
- satellite images
- remotely sensed
- support vector
- sparse coding
- error correcting output codes
- high dimensionality
- classification accuracy
- object detection
- machine learning
- dictionary learning
- svm classifier
- pairwise
- multiple classes
- neural network
- naive bayes
- model selection
- feature set
- dimensionality reduction
- principal component analysis
- data sets
- visual words
- feature space
- group lasso
- image segmentation
- earth observation
- multi class classifier