A High-Resolution, Random Forest Approach to Mapping Depth-to-Bedrock across Shallow Overburden and Post-Glacial Terrain.
Shane FurzeAntóin M. O'SullivanSerge AllardToon PronkR. Allen CurryPublished in: Remote. Sens. (2021)
Keyphrases
- random forest
- high resolution
- low resolution
- depth map
- random forests
- feature set
- decision trees
- feature importance
- fold cross validation
- remote sensing
- super resolution
- image processing
- rotation forest
- ensemble methods
- multi label
- multiresolution
- natural language processing
- ensemble learning
- machine learning
- knn
- data sets
- computer vision
- neural network
- decision tree learning algorithms
- benchmark datasets
- text categorization
- image classification
- information extraction
- high dimensional
- face recognition
- feature selection