Learning change from synthetic aperture radar images: performance evaluation of a support vector machine to detect earthquake and tsunami-induced changes
This study evaluates the performance of a Support Vector Machine (SVM) classifier to learn and detect changes in single- and multi-temporal X- and L-band Synthetic Aperture Radar (SAR) images under varying conditions. The purpose is to provide guidance on how to train a powerful learning machine for...
| मुख्य लेखकों: | , , |
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| स्वरूप: | Journal article |
| प्रकाशित: |
MDPI
2016
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