Learning Relevant Image Features With Multiple-Kernel Classification

  title={Learning Relevant Image Features With Multiple-Kernel Classification},
  author={Devis Tuia and Gustavo Camps-Valls and Giona Matasci and Mikhail F. Kanevski},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
The increase in spatial and spectral resolution of the satellite sensors, along with the shortening of the time-revisiting periods, has provided high-quality data for remote sensing image classification. However, the high-dimensional feature space induced by using many heterogeneous information sources precludes the use of simple classifiers: thus, a proper feature selection is required for discarding irrelevant features and adapting the model to the specific problem. This paper proposes to… CONTINUE READING
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