Offshore Oil Spill Detection Based on CNN, DBSCAN, and Hyperspectral Imaging [PDF]
Offshore 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
Comparative analysis of the performance of mixing rules for density prediction of simple chemical mixtures [PDF]
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
Oil Spill Detection Using Satellite Imagery [PDF]
Since oil exploration began, oil spills have become a serious problem. When drilling for oil, there is always a risk of an oil spill. With the new development of technology over the years, oil spill detection has become much easier making the clean-up of a spill to happen much faster reducing the risk of a large spread.
Amber Bonnington +2 more
openaire +1 more source
Hyperspectral Marine Oil Spill Monitoring Using a Dual-Branch Spatial–Spectral Fusion Model
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
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
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
Oil Spill Detection with Multiscale Conditional Adversarial Networks with Small-Data Training
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 +1 more source
Marine Oil Spill Detection from Low-Quality SAR Remote Sensing Images
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
OIL SPILL AISA+ HYPERSPECTRAL DATA DETECTION BASED ON DIFFERENT SEA SURFACE GLINT SUPPRESSION METHODS [PDF]
The marine oil spill is a sudden event, and the airborne hyperspectral means to detect the oil spill is an important part of the rapid response. Sun glint, the specular reflection of sun light from water surface to sensor, is inevitable due to the ...
J. Yang +5 more
doaj +1 more source
Underwater Pipeline Oil Spill Detection Based on Structure of Root and Branch Cells
The existing oil spill detection methods mainly rely on physical sensors or numerical models cannot locate the spill position accurately and in time. To solve this problem, combining with underwater image processing technology, an unsupervised detection ...
Huajun Song, Jie Song, Peng Ren
doaj +1 more source

