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Categoria WoS
Titulo: Automatic Fish Segmentation on Vertical Slot Fishways Using SOM Neural Networks
Tipo: congreso nacional
Congreso: International Work Conference on Artificial Neural Network (IWANN)
Fecha: 12-14/6/2013
Lugar celebracion: Puerto de La Cruz
Volumen: IWANN 2013, Parte I
Paginas: 445-452
ISBN: 978-3-642-38678-7
Libro: LNCS 7902
Editorial: Springer Heidelberg


Vertical slot fishways are hydraulic structures which allow the up-stream migration of fish through obstructions in rivers. The appropriate design of these should consider the behavior and biological variable of the target fish species and currently existing mechanisms to measure the behavior of the fish in these assays, cuch as direct observation or placement of sensors on the speciments , are impractical or unduly affect the animal beahavior. This paper studies the application of Artificial Neural networks to the problema of automatic fish segmentation in vertical slot sishways. In particular, SOM Neural networks have been used to detect fishes using visual information sampled by and underwater camera system. A ground true dataset was designed with expersts and different approaches were tested providing promising results.

    .: SABIA :.  Sistemas Adaptativos y Bioinspirados en Inteligencia Artificial