A Semi-Supervised Model for Fine-Grained Identification of Oil Emulsions on the Sea Surface Using Hyperspectral Imaging

After oil spills occur in the ocean, oil pollutants usually appear in the form of oil emulsions under the influence of hydrodynamics. Hyperspectral remote sensing technology, which provides abundant spectral information of ground objects, has the potential of fine-grained classification on the types...

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Veröffentlicht in:	Journal of the Indian Society of Remote Sensing 2024-09, Vol.52 (9), p.2083-2097
Hauptverfasser:	Xie, Ming, Gou, Tao, Dong, Shuang, Li, Ying
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks data collection Earth and Environmental Science Earth Sciences Emulsions Hydrodynamics Hyperspectral imaging image analysis Image classification Image filters Image segmentation Machine learning Marine pollution neural networks Oil pollution Oil spills oils Remote sensing Remote Sensing/Photogrammetry Research Article Seawater
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