A novel deep learning method for marine oil spill detection from satellite synthetic aperture radar imagery

X Huang, B Zhang, W Perrie, Y Lu, C Wang - Marine Pollution Bulletin, 2022 - Elsevier
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 …

Quad-polarimetric SAR sea state retrieval algorithm from Chinese Gaofen-3 wave mode imagettes via deep learning

H Wang, J Yang, M Lin, W Li, J Zhu, L Ren… - Remote Sensing of …, 2022 - Elsevier
Synthetic aperture radar (SAR) is a powerful tool for monitoring sea states in terms of the
significant wave height (SWH). Regarding the specific wave mode, to date, the previous …

Sea ice extraction via remote sensed imagery: Algorithms, datasets, applications and challenges

A Yu, W Huang, Q Xu, Q Sun, W Guo, S Ji… - arXiv preprint arXiv …, 2023 - arxiv.org
The deep learning, which is a dominating technique in artificial intelligence, has completely
changed the image understanding over the past decade. As a consequence, the sea ice …

Deep learning for predicting significant wave height from synthetic aperture radar

B Quach, Y Glaser, JE Stopa… - … on Geoscience and …, 2020 - ieeexplore.ieee.org
The Sentinel-1 satellites equipped with synthetic aperture radars (SARs) provide near-
global coverage of the world's oceans every six days. We curate a data set of collocations …

Autoablation: Automated parallel ablation studies for deep learning

S Sheikholeslami, M Meister, T Wang… - Proceedings of the 1st …, 2021 - dl.acm.org
Ablation studies provide insights into the relative contribution of different architectural and
regularization components to machine learning models' performance. In this paper, we …

Prediction of categorized sea ice concentration from Sentinel-1 SAR images based on a fully convolutional network

I De Gelis, A Colin, N Longépé - IEEE Journal of Selected …, 2021 - ieeexplore.ieee.org
The consistent and long-term spaceborne synthetic aperture radar (SAR) missions such as
Sentinel-1 (S-1) provide high-quality dual-polarized C-band images particularly suited to …

Classification of the global Sentinel-1 SAR vignettes for ocean surface process studies

C Wang, P Tandeo, A Mouche, JE Stopa… - Remote Sensing of …, 2019 - Elsevier
Spaceborne synthetic aperture radar (SAR) can provide finely-resolved (meters-scale)
images of ocean surface roughness day-or-night in nearly all weather conditions. This …

Semantic segmentation of metoceanic processes using SAR observations and deep learning

A Colin, R Fablet, P Tandeo, R Husson, C Peureux… - Remote Sensing, 2022 - mdpi.com
Through the Synthetic Aperture Radar (SAR) embarked on the satellites Sentinel-1A and
Sentinel-1B of the Copernicus program, a large quantity of observations is routinely …

[HTML][HTML] Sea Ice Extraction via Remote Sensing Imagery: Algorithms, Datasets, Applications and Challenges

W Huang, A Yu, Q Xu, Q Sun, W Guo, S Ji, B Wen… - Remote Sensing, 2024 - mdpi.com
Deep learning, which is a dominating technique in artificial intelligence, has completely
changed image understanding over the past decade. As a consequence, the sea ice …

Marine environmental impact on CFAR ship detection as measured by wave age in SAR images

DX Bezerra, JA Lorenzzetti, RL Paes - Remote Sensing, 2023 - mdpi.com
Satellite synthetic aperture radar (SAR) images are recognized as one of the most efficient
tools for day/night, all weather and large area monitoring of ships at sea. However, false …