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Digital archive of theses discussed at the University of Pisa

 

Thesis etd-09032020-103706


Thesis type
Tesi di laurea magistrale
Author
CABRAS, ALESSANDRO
URN
etd-09032020-103706
Thesis title
Design and implementation of an efficient orbital debris detection in astronomical images using Deep Learning
Department
INGEGNERIA DELL'INFORMAZIONE
Course of study
COMPUTER ENGINEERING
Supervisors
relatore Prof. Falchi, Fabrizio
relatore Prof. Gennaro, Claudio
relatore Prof. Amato, Giuseppe
correlatore Dott. Pisanu, Tonino
correlatore Ing. Panico, Alessandro
Keywords
  • Machine learning
  • Object detection
  • Orbital debris
  • Tracking
  • Yolo
Graduation session start date
25/09/2020
Availability
None
Summary
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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