Identificador persistente para citar o vincular este elemento: https://accedacris.ulpgc.es/handle/10553/139382
Título: Advanced AI Strategies for Coastal Analysis: A Case Study at Las Canteras Beach in Gran Canaria
Autores/as: Sanfiel Reyes, Fernando 
Suárez Ramírez, Jonay 
Alemán-Flores, Miguel 
Monzón, Nelson 
Clasificación UNESCO: 251010 Procesos litorales o sublitorales
120304 Inteligencia artificial
Palabras clave: Coastal Dynamic
Deep Learning
Semantic Segmentation
Fecha de publicación: 2025
Editor/a: Universitat Politècnica de Catalunya 
Proyectos: Detección precisa mediante Inteligencia Artificial deeventos de interés en escenas de playa, costa y litoral. 
Publicación seriada: Instrumentation viewpoint 
Conferencia: MARTECH 25 : 12th International Workshop on Marine Technology
Resumen: We propose a semantic segmentation model to analyze coastal dynamics. Using advanced AI techniques, precise segmentation masks are generated, overcoming challenges like changing weather conditions, glare, or shadows. A diverse dataset ensures adaptability, classifying features such as waves, sand, foam, and static infrastructures at the pixel level. This enables detailed analysis of interactions between marine elements and coastal structures, and can lead to measurements such as wave period, crucial for predicting overtopping events and identifying abnormal sea behavior. Experiments at Las Canteras Beach in Gran Canaria, a location where our model was not trained, yet it still performed well, demonstrate its effectiveness. This research illustrates AI's potential in advancing coastal management and environmental monitoring.
URI: https://accedacris.ulpgc.es/handle/10553/139382
ISBN: 978-84-09-61714-2
ISSN: 1886-4864
Fuente: Martech 2025. Marine Technology Workshop, p. 19-20. 28th - 29th May. Pasaia (Gipuzkoa), Spain
Colección:Actas de congresos
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