FASTER TREES: STRATEGIES FOR ACCELERATED TRAINING AND PREDICTION OF RANDOM FORESTS FOR CLASSIFICATION OF POLSAR IMAGES
Random Forests have continuously proven to be one of the most accurate, robust, as well as efficient methods for the supervised classification of images in general and polarimetric synthetic aperture radar data in particular. While the majority of previous work focus on improving classification accu...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2018-04-01
|
| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-3/105/2018/isprs-annals-IV-3-105-2018.pdf |