Spatio-Temporal Clustering and Active Learning for Change Classification in Satellite Image Time Series.
Nicolas DebonnaireAndré StumpfAnne PuissantPublished in: IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2016)
Keyphrases
- satellite images
- spatio temporal
- active learning
- selective sampling
- pattern recognition
- remote sensing
- remotely sensed
- remotely sensed imagery
- text classification
- support vector machine
- change detection
- supervised learning
- multispectral
- multivariate time series data
- clustering algorithm
- batch mode active learning
- machine learning
- supervised classification
- land cover
- multivariate time series
- unsupervised learning
- data sets
- decision trees
- image sequences
- support vector
- training set
- random selection
- semi supervised
- image processing
- neural network
- image analysis
- hyperspectral
- remote sensing images
- moving objects
- high resolution
- spatial and temporal
- high quality
- digital elevation models
- clustering method
- active learning framework