Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/38624
Title: Support Tucker machines based marine oil spill detection using SAR images
Authors: Ma, Liyong
Keywords: Oil spill detection;Classification;Support Tucker machines;SAR image
Issue Date: Nov-2016
Publisher: NISCAIR-CSIR, India
Abstract: Marine oil spills can destroy wildlife habitat, breeding ground and pollute the sea water or beaches. It is critical to detect marine oil spills efficiently and distinguish the oil spills from other look-alike objects before the clean action. Employing support Tucker machines, a learning based method is proposed for the detection of marine oil spills with SAR images. Firstly the features are obtained from the original images, and a tensor is constructed from the exacted features and the image. Subsequently support Tucker machines are employed for classification training with labeled samples. Lastly the trained support Tucker machines are employed for marine oil spills detection. The experimental results demonstrate that our proposed method is promising and superior to artificial neural network and support vector machines based methods in accuracy.
Page(s): 1445-1449
URI: http://nopr.niscair.res.in/handle/123456789/38624
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections:IJMS Vol.45(11) [November 2016]

Files in This Item:
File Description SizeFormat 
IJMS 45(11) 1445-1449.pdf198.41 kBAdobe PDFView/Open


Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.