Automatic detection of Moroccan coastal upwelling from chlorophyll-a concentration images using the Expectation-Maximization method
Author:
Affiliation:
1. Mohammed V university,LRIT-CNRST URAC 29, Faculty of sciences In Rabat,Morocco
2. Mohammed V university,LRIT-CNRST URAC 29, Rabat IT Center, Faculty of sciences In Rabat,Morocco
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9800204/9800205/09800206.pdf?arnumber=9800206
Reference16 articles.
1. A simple tool for automatic extraction of Moroccan coastal upwelling from Sea Surface Temperature images
2. Detection of Moroccan coastal upwelling in SST images using the Expectation-Maximization
3. A Simple Fusion Approach of Chlorophyll Images and Sea Surface Temperature Images for Improving the Detection of Moroccan Coastal Upwelling
4. Delineation of Moroccan Coastal Upwelling Using The Principal Component Analysis Fusion Algorithm on SSC and SST Images
5. Detection of Moroccan coastal upwelling using the alpha blending fusion technique of sea surface chlorophyll images and sea surface temperature images
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1. Monitoring upwelling regions in major coastal zones using deep learning and sea surface temperature images;International Journal of Remote Sensing;2024-06-28
2. Delineation of Upwelling along the Northwest African coast using Attention-Coastalup-Net.;2024 IEEE 12th International Symposium on Signal, Image, Video and Communications (ISIVC);2024-05-21
3. Advanced Deep Learning Approach for Accurate Upwelling Detection Along Morocco’s Atlantic Coast Using SST Imagery;IEEE Geoscience and Remote Sensing Letters;2024
4. DeepRes-UpwellNet: A Robust Framework for Coastal Upwelling Monitoring Along the Moroccan Atlantic Coast;2023 IEEE International Conference on Advances in Data-Driven Analytics And Intelligent Systems (ADACIS);2023-11-23
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