A Two-Stage Deep Learning Method for Marine Oil Spill Localization and Segmentation From Synthetic Aperture Radar Images
Oil spills have devastating impacts on ocean ecosystems, leading to significant economic losses. Consequently, it is crucial to develop effective techniques for the rapid detection of marine oil spills using satellite observations. Existing methods for detecting oil spills using synthetic aperture r...
Saved in:
| Main Authors: | Xudong Huang, Biao Zhang, William Perrie |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10990149/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Spectral-Spatial Collaborative Pretraining Framework With Multiconstraint Cooperation for Hyperspectral–Multispectral Image Fusion
by: Jia Jia, et al.
Published: (2025-01-01) -
C-Band Q-Switched Fiber Laser Using Titanium Dioxide (TiO 2) As Saturable Absorber
by: H. Ahmad, et al.
Published: (2016-01-01) -
Secrecy Performance Analysis of Mixed <italic>α</italic> − <italic>μ</italic> and Exponentiated Weibull RF-FSO Cooperative Relaying System
by: Nazmul Hassan Juel, et al.
Published: (2021-01-01) -
MoS$_2$ Broadband Coherent Perfect Absorber for Terahertz Waves
by: Weiren Zhu, et al.
Published: (2016-01-01) -
Robust Extended <italic>H<sub>∞</sub></italic> Control Strategy Using Linear Matrix Inequality Approach for Islanded Microgrid
by: Maniza Armin, et al.
Published: (2020-01-01)