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LSTOP - Learning Spatio-Temporal Oceanographic Patterns

Project information

The main objective of this project is the development of Machine Learning methods for the automatic identification, analysis and prediction of oceanographic mesoscale phenomena in the Iberian Coastal Ocean (eddies, upwelling and coastal counter-current), including their spatio-temporal evolution, from remote sensing images. Dynamic versions of fuzzy clutstering will be investigated in the identification and tracking of these phenomena, and knowledge-aware neural networks will be studied for their classification and prediction incorporating domain knowledge.

Ongoing since February 2008, concludes in January 2011.


Principal researcher: Fátima Sousa.

Researchers: Joaquim Dias, Igor Bashmachnikov.


Funding entity: Fundação Ciência e Tecnologia (MCTES).

Reference: PTDC/EIA/68183/2006


Principal researcher: Susana Nascimento.

Researchers: Armando Fernandes (2008-2009), Nuno C. Marques, Davide D'Alimonte.

Funding: € 109 321.

Centre for Artificial Intelligence of UNL
Departamento de Informática, FCT/UNL
Quinta da Torre 2829-516 CAPARICA - Portugal
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