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Artificial intelligence for applications in eco-hydraulics

keywords COLLECTIVE BEHAVIOUR, DEEP LEARNING, FISH

Reference persons COSTANTINO MANES

Thesis type DATA ANALYSIS

Description The student will train and apply a neural network to analyze images taken from videos grabbing the behaviour of fish schools in an experimental flume. The output from the neural network will help tracking the fish coordinates' in time and hence investigate their collective behaviour under various hydrodynamic conditions. The topic is extremely relevant to model migrating fish behaviour in proximity of fishways.

Required skills Fundamentals of fluid mechanics, basic programming skills


Deadline 11/12/2023      PROPONI LA TUA CANDIDATURA




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