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Projecte matriculat

Títol: Spectral automated classification in large databases

Director: REBASSA MANSERGAS, Alberto

Departament: FIS

Títol: Spectral automated classification in large databases

Data inici oferta: 26-06-2020     Data finalització oferta: 26-02-2021


Estudis d'assignació del projecte:
    DG ENG AERO/SIS TEL
    DG ENG AERO/TELEMÀT
    DG ENG SISTE/TELEMÀT
Tipus: Individual
 
Lloc de realització: EETAC
 
Segon director (UPC): TORRES GIL, Santiago
 
Paraules clau:
databases, artificial intelligence, spectroscopy
 
Descripció del contingut i pla d'activitats:
Pattern recognition in large databases relying on automated
artificial intelligent methods is one of the most challenging
problems in science and technology today. Although its
theoretical grounds may be the same, its applications are
enormously varied: voice recognition, image analysis, signal
processing, are a few examples.

In particular, spectroscopy recognition and analysis is without
any doubt one of the most valuable observational techniques in
modern astronomy. In a few months, the Gaia satellite launched
by the European Space Agency will release spectra of more than
300 million stars in our Galaxy, thus opening a new exciting era
for stellar spectroscopy. However, given the large amount of
data, an automated spectral classification is required. This TFG
will consist on developing the necessary tools, via artificial
intelligence techniques, for such an automated spectral
classification and their implementation. In a first step,
the algorithm will be tested with known synthetic data. Once the
machine learning process has been proven efficient, it will be
applied to real databases.
 
Orientació a l'estudiant:
matlab/fortran/python are recommended.

 
Requereix activitats hardware: No
 
Requereix activitats software: No
 
Horari d'atenció a estudiants per a l'assignació de projecte:

Data de generació 10/05/2021