Classification of Large-Scale High-Resolution SAR Images with Deep Transfer Learning

6 Jan 2020Zhongling HuangCorneliu Octavian DumitruZongxu PanBin LeiMihai Datcu

The classification of large-scale high-resolution SAR land cover images acquired by satellites is a challenging task, facing several difficulties such as semantic annotation with expertise, changing data characteristics due to varying imaging parameters or regional target area differences, and complex scattering mechanisms being different from optical imaging. Given a large-scale SAR land cover dataset collected from TerraSAR-X images with a hierarchical three-level annotation of 150 categories and comprising more than 100,000 patches, three main challenges in automatically interpreting SAR images of highly imbalanced classes, geographic diversity, and label noise are addressed... (read more)

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