Oil leaks onto water surfaces from big tankers, ships, and pipeline cracks cause
considerable damage and harm to the marine environment. Synthetic Aperture Radar (SAR) …

We propose a deep-learning framework to detect and categorize oil spills in synthetic
aperture radar (SAR) images at a large scale. Through a carefully designed neural network …

Oil spill is considered one of the main threats to marine and coastal environments. Efficient
monitoring and early identification of oil slicks are vital for the corresponding authorities to …

Oil spill discharges from operational maritime activities like ships, oil rigs and other
structures, leaking pipelines, as well as natural hydrocarbon seepage pose serious threats …

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 …

One of the major threats to marine ecosystems is pollution, particularly, that associated with
the offshore oil and gas industry. Oil spills occur in the world's oceans every day, either as …

Oil spill pollution comprises a significant threat of the oceanic and coastal ecosystems. A
continuous monitoring framework with automatic detection capabilities could be valuable as …

The frequency of marine oil spills has increased in recent years. The growing exploitation of
marine oil and continuous increase in marine crude oil transportation has caused …

Oil spills pose a major threat of the oceanic and coastal environments, hence, an automatic
detection and a continuous monitoring system comprises an appealing option for minimizing …

Classification algorithms for automatically detecting sea surface oil spills from spaceborne
Synthetic Aperture Radars (SARs) can usually be regarded as part of a three-step …