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
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
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
Remote Sensing, 2019 Synthetic aperture radar (SAR) is an important means to detect ocean oil spills which cause serious damage to the marine ecosystem. However, the look-alikes, which have a similar behavior to oil slicks in SAR images, will reduce the oil spill detection ...
Shengwu Tong +4 more
doaj +3 more sources
Large-Scale Detection and Categorization of Oil Spills from SAR Images with Deep Learning
Remote Sensing, 2020 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 model for image segmentation trained on an extensive dataset, we obtain state ...
Filippo Maria Bianchi +2 more
doaj +3 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
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
OIL SPILL AISA+ HYPERSPECTRAL DATA DETECTION BASED ON DIFFERENT SEA SURFACE GLINT SUPPRESSION METHODS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 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