Journal
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
Volume 38, Issue 5, Pages 2282-2287Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/36.868885
Keywords
ERS-synthetic aperture radar (SAR); neural networks; oil spill detection
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A neural network approach for semi-automatic detection of oil spills in European remote sensing satellite-synthetic aperture radar (ERS-SAR) imagery is presented, The network input is a vector containing the values of a set of features characterizing an oil spill candidate. The classification performance of the algorithm has been evaluated on a data set containing verified examples of oil spill and look-alike, A direct analysis of the information content of the calculated features has been also carried out through an extended pruning procedure of the net.
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