IIIE   20352
INSTITUTO DE INVESTIGACIONES EN INGENIERIA ELECTRICA "ALFREDO DESAGES"
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Coastal Monitoring: Classification of beach areas using machine learning techniques
Autor/es:
DYLAN S. LASSO; GIAN MAVO; CLAUDIO DELRIEUX; NATALIA V. REVOLLO; GERARDO PERILLO
Lugar:
Valdivia
Reunión:
Conferencia; Conference: XV IEEE Latin-American Summer School on Computational Intelligence; 2019
Resumen:
Beaches are highly dynamic environments, wherecomplex modifications occur in a wide range of space-time scales.For this reason, and in order to study its dynamics and morphology, continuous monitoring is required. In the last decades,remote monitoring systems have proven to be an alternativefor this and other similar purposes. In this work, classificationmethods were used using machine learning techniques, withvideos taken from Pehuen-C ´ o beach (Argentina). Different beach ´zones were automatically classified according to domain expertscriteria, achieving an accuracy over 92 %.