A Novel Object-Based Supervised Classification Method with Active Learning and Random Forest for PolSAR Imagery.
Wensong LiuJie YangPingxiang LiYue HanJinqi ZhaoHongtao ShiPublished in: Remote. Sens. (2018)
Keyphrases
- classification method
- random forest
- active learning
- semi supervised
- supervised learning
- learning algorithm
- random forests
- decision trees
- machine learning
- classification algorithm
- knn
- computer vision
- decision tree learning algorithms
- text classification
- support vector machine
- selective sampling
- selected features
- k nearest neighbor
- feature set
- support vector machine svm
- labeled data
- training set
- unsupervised learning
- semi supervised learning
- unlabeled data
- ensemble methods
- neural network
- high resolution
- random sampling
- fold cross validation
- training examples
- multi label
- clustering algorithm
- ensemble classifier
- base classifiers
- naive bayes
- text mining
- support vector
- image processing
- feature selection
- relevance feedback
- text categorization
- nearest neighbor
- learning process
- pattern recognition