Artificial Intelligence for Marine SAR Oil-Slicks Detection
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-70018-7_24
Reference9 articles.
1. Fingas, M., Brown, C.: Review of oil spill remote sensing. Marine Pollution Bulletin 83(1), 9–23 (2014)
2. Topouzelis, K.N.: Oil spill detection by SAR images: dark formation detection, feature extraction and classification algorithms. J. Sensors (8), 6642–6659 (2008). https://doi.org/10.3390/s8106642, ISSN 1424-8220 (2008)
3. Topouzelis, V., Pavlakis, P., Rokos, D.: Dark formation detection using neural networks. Int. J. Remote Sensing 29, 4705–4720 (2008)
4. Lounis, B., Mercier, G., Belhadj-aissa, A.: Combination of statistical similarity measure and derivative morphological profile approach for oil slick detection in SAR images. J. Math. Modelling Algorithms JMMA 11(4), 409–432 (2012). https://doi.org/10.1007/s10852-012-9206-4
5. Lounis, B., Lacheb, N., Smara, Y., A. Belhadj-Aissa, Y.: Adapting neuro fuzzy system for Oil spills detection from sea SAR images. In: IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium, Tunisia March 9–11, 2020, Tunis, Tunisia (2020)
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