Improving the accuracy of random forest-based land-use classification using fused images and digital surface models produced via different interpolation methods.
Alper AkarPublished in: Concurr. Comput. Pract. Exp. (2022)
Keyphrases
- random forest
- fold cross validation
- decision trees
- classification accuracy
- feature set
- interpolation methods
- decision tree learning algorithms
- classification models
- machine learning methods
- machine learning
- image interpolation
- machine learning algorithms
- ensemble classifier
- support vector machine
- neural network
- training set
- ensemble methods
- feature selection
- feature vectors
- benchmark datasets
- object recognition
- base classifiers
- support vector
- feature extraction
- image processing
- interpolation method
- digital surface