ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-05012020-101143


Tipo di tesi
Tesi di dottorato di ricerca
Autore
PAVONI, GAIA
URN
etd-05012020-101143
Titolo
AUTOMATIZING THE LARGE-SCALE ANALYSIS OF UNDERWATER OPTICAL DATA
Settore scientifico disciplinare
ING-INF/04
Corso di studi
INGEGNERIA DELL'INFORMAZIONE
Relatori
tutor Prof. Pollini, Lorenzo
relatore Prof. Caiti, Andrea
relatore Dott. Corsini, Massimiliano
Parole chiave
  • Intelligent tools
  • human-in-the -loop
  • Automatic recognition
Data inizio appello
04/05/2020
Consultabilità
Non consultabile
Data di rilascio
04/05/2023
Riassunto
Underwater monitoring provides essential information to analyze the current condition and persisting trends of marine habitats. The optical data acquisition is a powerful solution to ensure both high-resolution and large-scale sampling of the seafloor. The use of autonomous data-driven robotics is making underwater imaging more and more popular. Nevertheless, video and image sequences are a trustworthy source of knowledge that remains partially unexploited: the human visual analysis of images is a very time-consuming task, which creates a bottleneck between data collection and extrapolation.
This thesis presents a human-in-the-loop software solution, based on deep learning methodologies and computer vision, suitable for supporting and speeding up the analysis of visual data coming from underwater environmental monitoring activities.
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