An Ensemble of Classifiers Based on Positive and Unlabeled Data in One-Class Remote Sensing Classification.
Ran LiuWenkai LiXiaoping LiuXingcheng LuTianhong LiQinghua GuoPublished in: IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2018)
Keyphrases
- remote sensing
- ensemble classifier
- multiple classifiers
- majority voting
- multi spectral images
- land cover classification
- change detection
- supervised classification
- training set
- remotely sensed
- individual classifiers
- classifier ensemble
- hyperspectral images
- remote sensing imagery
- remote sensing images
- feature selection
- multispectral
- hyperspectral
- hyperspectral data
- land cover
- remote sensing data
- decision trees
- combining classifiers
- ensemble learning
- image analysis
- high resolution
- machine learning methods
- training data
- training samples
- satellite images
- svm classifier
- remotely sensed images
- multiple classifier systems
- high spatial resolution
- satellite imagery
- remotely sensed data
- ensemble methods
- weak classifiers
- image fusion
- class labels
- classifier combination
- pattern recognition
- image processing
- earth observation
- machine learning
- geographical information systems
- learning algorithm
- feature set
- support vector machine
- satellite data
- automatic image registration
- digital image analysis
- pixel classification
- hyperspectral imagery
- base classifiers
- feature space
- bayesian classifier
- multi class
- image classification
- feature vectors
- hyperspectral imaging
- neural network
- remote sensed images