ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-09032020-103706


Tipo di tesi
Tesi di laurea magistrale
Autore
CABRAS, ALESSANDRO
URN
etd-09032020-103706
Titolo
Design and implementation of an efficient orbital debris detection in astronomical images using Deep Learning
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
COMPUTER ENGINEERING
Relatori
relatore Prof. Falchi, Fabrizio
relatore Prof. Gennaro, Claudio
relatore Prof. Amato, Giuseppe
correlatore Dott. Pisanu, Tonino
correlatore Ing. Panico, Alessandro
Parole chiave
  • Orbital debris
  • Object detection
  • Yolo
  • Machine learning
  • Tracking
Data inizio appello
25/09/2020
Consultabilità
Tesi non consultabile
Riassunto
Widefield telescopes, that work in staring mode, are widely used for optical astronomical observations. In the observed images, the identification of moving objects, visible as linear features (streaks), is important for several reasons including the cataloging of space debris.
This thesis work consists in the design and development of a system based on machine learning approaches that identify these objects in real-time in the shortest possible time and returns their position within the image through bounding boxes.
This result will be useful for the realization of a tracking system that predicts the direction of movement of the debris and communicates with a second, reduced FOV, telescope that follows it.
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