Land cover analysis of PolSAR images using probabilistic voting ensemble and integrated support vector machine
Author:
Affiliation:
1. Military Technical College, Aircraft Electrical Equipment Department, Cairo, Egypt
2. National Authority of Remote Sensing and Space Sciences, Cairo, Egypt
Publisher
SPIE-Intl Soc Optical Eng
Subject
General Earth and Planetary Sciences
Reference30 articles.
1. Land cover classification of PolSAR image using tensor representation and learning
2. Unsupervised classification of PolSAR image based on tensor product graph diffusion
3. Unsupervised Multi-level Segmentation Framework for PolSAR Data using H-Alpha features and the Combined Edge- Region based segmentation
4. Classification of multi-look polarimetric SAR imagery based on complex Wishart distribution
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