Zobrazeno 1 - 10
of 47
pro vyhledávání: '"dark spot detection"'
Publikováno v:
IEEE Access, Vol 12, Pp 30254-30262 (2024)
Dark spot detection is an important and fundamental step in oil spill detection, which affects the accuracy of oil spill detection. In this paper, a Multiple-Try Markov Chain Monte Carlo (MTMCMC)-based dark spot detection method is presented under th
Externí odkaz:
https://doaj.org/article/627432a24344465ba2d4095f6183915f
Publikováno v:
European Journal of Remote Sensing, Vol 55, Iss 1, Pp 181-198 (2022)
Oil spill detection (OSD) in marine areas is an application of synthetic aperture radar (SAR) images to protect aquatic life. In this paper, a new oil spill detection algorithm based on level set method (LSM) is presented. Dark spot detection, featur
Externí odkaz:
https://doaj.org/article/d21cd4b9361c44daa4a88ba2c8304ae1
Publikováno v:
Remote Sensing, Vol 14, Iss 21, p 5618 (2022)
Synthetic Aperture Radar (SAR) is the primary equipment used to detect oil slicks on the ocean’s surface. On SAR images, oil spill regions, as well as other places impacted by atmospheric and oceanic phenomena such as rain cells, upwellings, and in
Externí odkaz:
https://doaj.org/article/23465003248d48d983e411fc76a6336d
Akademický článek
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Akademický článek
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Autor:
Rami Al-Ruzouq, Mohamed Barakat A. Gibril, Abdallah Shanableh, Abubakir Kais, Osman Hamed, Saeed Al-Mansoori, Mohamad Ali Khalil
Publikováno v:
Remote Sensing, Vol 12, Iss 20, p 3338 (2020)
Remote sensing technologies and machine learning (ML) algorithms play an increasingly important role in accurate detection and monitoring of oil spill slicks, assisting scientists in forecasting their trajectories, developing clean-up plans, taking t
Externí odkaz:
https://doaj.org/article/6f4c8dbb7d674f67a03cd0ddc993abbf
Autor:
Alireza Taravat, Natascha Oppelt
Publikováno v:
Sensors, Vol 14, Iss 12, Pp 22798-22810 (2014)
Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection
Externí odkaz:
https://doaj.org/article/4587325972a7495b9546c9270242ef0c
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Publikováno v:
Remote Sensing; Volume 14; Issue 21; Pages: 5618
Synthetic Aperture Radar (SAR) is the primary equipment used to detect oil slicks on the ocean’s surface. On SAR images, oil spill regions, as well as other places impacted by atmospheric and oceanic phenomena such as rain cells, upwellings, and in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::785380c869ba461bb208d012fa9a723a
https://doi.org/10.3390/rs14215618
https://doi.org/10.3390/rs14215618
Autor:
Osman Hamed, Mohamed Barakat A. Gibril, Mohamad Ali Khalil, Abdallah Shanableh, Saeed Al-Mansoori, Rami Al-Ruzouq, Abubakir Kais
Publikováno v:
Remote Sensing, Vol 12, Iss 3338, p 3338 (2020)
Remote sensing technologies and machine learning (ML) algorithms play an increasingly important role in accurate detection and monitoring of oil spill slicks, assisting scientists in forecasting their trajectories, developing clean-up plans, taking t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::573cfeb67855427c9a7766bb8a51cfe7
https://www.mdpi.com/2072-4292/12/20/3338
https://www.mdpi.com/2072-4292/12/20/3338