Transformer-Based Deep Learning for Mesoscale Eddy Detection in Sea Surface Temperature Maps
Mesoscale eddies are dynamic oceanic phenomena significantly influencing marine ecosystems’ energy transfer, nutrients, and biogeochemical cycles. These eddies’ precise identification and categorization can improve climate modeling, ocean circulation research, and environmental...
Saved in:
Main Authors: | Chen Ji, Wenyang Xu, Xiangtian Zheng, Yasmeen Ahmed, Saad Ahmed Jamal, Fakhar Imam, Mohammed Saleh Ali Muthanna, Maha Ibrahim, Sajid Ullah, Dmitry E. Kucher |
---|---|
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/11015982/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Development of a rapid fiber-detection system using artificial intelligence in phase-contrast microscope images of actual atmospheric samples
by: Yukiko Iida, et al.
Published: (2025-06-01) -
GCSA-SegFormer: Transformer-Based Segmentation for Liver Tumor Pathological Images
by: Jingbin Wen, et al.
Published: (2025-06-01) -
SMoFFI-SegFormer: a novel approach for ovarian tumor segmentation based on an improved SegFormer architecture
by: Qiuyin Xie, et al.
Published: (2025-07-01) -
Impacts of Weak Sea Surface Temperature Warm Anomalies on Local Trade Cumulus Cloudiness in Large Eddy Simulations
by: Xuanyu Chen, et al.
Published: (2025-07-01) -
Marine Heatwaves and Cold Spells Accompanied by Mesoscale Eddies Globally
by: Sifan Su, et al.
Published: (2025-07-01)