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