Gabriele Moreno Berton
CNN-based method with self-supervision for visual place recognition.
Rel. Barbara Caputo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (10MB) | Preview |
Abstract
An open problem in the artificial intelligence community is built an algorithm to able geo-localize a given photo, overcoming the multiple problems related to the domain shift between the images used during the training and the ones passed at test time. During this thesis, our contribution didn’t just focus on research but we have also implemented a software that is easy to use for any kind of user, as well as creating a dataset that can be used for further research. In order to exploit the VPR problem with a deep learning method, we have used the current state-of-the-art CNN called NetVLAD [1], that we have properly modified to speed up the process and for studying the results on our dataset.
In particular, we have tested the final network with a third-domain dataset and tried also a self-supervision approach, to make the network more confident with the different domains belong to training and testing phases
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
URI
![]() |
Modifica (riservato agli operatori) |
