Comparing CNNs and Random Forests for Landsat Image Segmentation Trained on a Large Proxy Land Cover Dataset.
Tony BostonAlbert I. J. M. van DijkPablo Rozas LarraondoRichard ThackwayPublished in: Remote. Sens. (2022)
Keyphrases
- random forests
- land cover
- multispectral
- image segmentation
- satellite images
- supervised classification
- remote sensing images
- remote sensing data
- satellite imagery
- remotely sensed
- random forest
- remote sensing
- change detection
- image analysis
- decision trees
- ensemble methods
- remotely sensed images
- logistic regression
- image data
- machine learning algorithms
- multispectral images
- graph cuts
- image processing
- benchmark datasets
- geographic information systems
- hyperspectral
- decision tree ensembles
- training set
- feature set
- computer vision
- svm classifier
- database
- unsupervised learning
- image classification
- supervised learning
- relational databases
- reinforcement learning
- machine learning
- databases