Oil Spill Detection with Multiscale Conditional Adversarial Networks with Small-Data Training
Remote Sensing, 2021 We investigate the problem of training an oil spill detection model with small data. Most existing machine-learning-based oil spill detection models rely heavily on big training data.
Yongqing Li +3 more
doaj +3 more sources
Offshore Oil Spill Detection Based on CNN, DBSCAN, and Hyperspectral Imaging [PDF]
SensorsOffshore oil spills have the potential to inflict substantial ecological damage, underscoring the critical importance of timely offshore oil spill detection and remediation.
Ce Zhan +3 more
doaj +2 more sources
Sensors, Features, and Machine Learning for Oil Spill Detection and Monitoring: A Review
Remote Sensing, 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 ...
Rami Al-Ruzouq +6 more
doaj +3 more sources
Marine Oil Spill Detection from SAR Images Based on Attention U-Net Model Using Polarimetric and Wind Speed Information. [PDF]
Int J Environ Res Public Health, 2022 Chen Y, Wang Z.
europepmc +2 more sources
Comparative analysis of the performance of mixing rules for density prediction of simple chemical mixtures [PDF]
Журнал інженерних наук, 2021 Four different mixing rules (MRs) in three equations of state (EOSs) have been used to account for the intermolecular forces of attraction between dissimilar molecules of different substances that form simple mixtures.
Babalola F. U., Akanji I. O., Oyegoke T.
doaj +1 more source
A Multifamily GLRT for Oil Spill Detection [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2017 This paper deals with detection of oil spills from multipolarization synthetic aperture radar images. The problem is cast in terms of a composite hypothesis test aimed at discriminating between the polarimetric covariance matrix (PCM) equality (absence of oil spills in the tested region) and the situation where the region under test exhibits a PCM with
Antonio De Maio +3 more
openaire +5 more sources
Hyperspectral Marine Oil Spill Monitoring Using a Dual-Branch Spatial–Spectral Fusion Model
Remote Sensing, 2023 Marine oil spills pose a crucial concern in the monitoring of marine environments, and optical remote sensing serves as a vital means for marine oil spill detection.
Junfang Yang +5 more
doaj +1 more source
Preliminary Investigation on Marine Radar Oil Spill Monitoring Method Using YOLO Model
Journal of Marine Science and Engineering, 2023 Due to the recent rapid growth of ocean oil development and transportation, the offshore oil spill risk accident probability has increased unevenly. The marine oil spill poses a great threat to the development of coastal cities.
Bo Li +10 more
doaj +1 more source
Marine Oil Spill Detection with X-Band Shipborne Radar Using GLCM, SVM and FCM
Remote Sensing, 2022 Marine oil spills have a significant adverse impact on the economy, ecology, and human health. Rapid and effective oil spill monitoring action is extraordinarily important for controlling marine pollution.
Bo Li +7 more
doaj +1 more source
Marine Oil Spill Detection from Low-Quality SAR Remote Sensing Images
Journal of Marine Science and Engineering, 2023 Oil spills pose a significant threat to the marine ecological environment. The intelligent interpretation of synthetic aperture radar (SAR) remote sensing images serves as a crucial approach to marine oil spill detection, offering the potential for real ...
Xiaorui Dong +4 more
doaj +1 more source