A New Technique for Segmentation of the Oil Spills From Synthetic-Aperture Radar Images Using Convolutional Neural Network

A New Technique for Segmentation of the Oil Spills From Synthetic-Aperture Radar Images Using Convolutional Neural Network

Oil spills have proven to have detrimental effects on the marine-based environment and economy. Thus, it is necessary to identify oil spills and classify them in the sea to reduce oil-induced pollution in seas and oceans. Synthetic-aperture radar (SAR) imaging is a good option for rapid oil detectio...

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Bibliographic Details
Main Authors: Fatemeh Mahmoudi Ghara, Shahriar Baradaran Shokouhi, Gholamreza Akbarizadeh
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural networks (CNNs)
DEEPLABV3
feature extraction
oil spill
segmentation
synthetic aperture radar (SAR)
Online Access:https://ieeexplore.ieee.org/document/9916104/

Internet

https://ieeexplore.ieee.org/document/9916104/

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