An ensemble learning approach for the classification of remote sensing scenes based on covariance pooling of CNN features.
Sara AkodadSolène VilfroyLionel BombrunCharles C. CavalcanteChristian GermainYannick BerthoumieuPublished in: EUSIPCO (2019)
Keyphrases
- remote sensing
- ensemble learning
- ensemble classifier
- generalization ability
- weak learners
- remote sensing images
- classification accuracy
- feature vectors
- multi spectral images
- hyperspectral images
- feature set
- change detection
- multispectral
- classification models
- feature extraction
- feature space
- pattern recognition
- image analysis
- remote sensing data
- ensemble methods
- support vector machine
- image fusion
- remotely sensed data
- benchmark datasets
- high resolution
- hyperspectral
- image classification
- image features
- satellite images
- class labels
- land cover
- support vector
- machine learning
- feature subset
- svm classifier
- image processing
- learning algorithm
- random forest
- training examples
- feature selection
- hyperspectral remote sensing
- base classifiers
- classification algorithm
- k nearest neighbor
- fusion method
- face images
- prior knowledge
- training set
- neural network