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              <p>This paper addresses the problem of remote sensing image multi-scale classification by: (i) showing that us- ing multiple scales does improve classification results, but not all scales have the same importance; (ii) show- ing that image descriptors do not offer the same contri- bution at all scales, as commonly thought, and some of them are very correlated; (iii) introducing a simple ap- proach to automatically select segmentation scales, de- scriptors, and classifiers based on correlation and ac- curacy analysis.</p>
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