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Deep Learning Approach For Automatic Detection Of Oil Slicks
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, First EAGE/PESGB Workshop Machine Learning, Nov 2018, Volume 2018, p.1 - 3
Abstract
Summary
The aim of this study is to propose a deep learning approach for automatic oil slicks detection over surface of ocean based on Synthetic Aperture Radar (SAR) images. Deep networks such as U-Net is a kind of imagesegmentation- based algorithm which is proved to be effective for varies of image segmentation problems. Here we introduce an U-Net framework for our oil slicks segmentation task. Our database comes from SAR images of 5 differents regions over the world and is divided into training set and test set. With this U-Net structure, we have achieved an overall precision of 93% and a recall rate of 71% with our test set. The algorithm is able to distinguish between oil slicks and other object known as “lookalike”.
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