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Hauptverfasser: Hallopeau, Thomas, Guérin, Joris, Demagistri, Laurent, Fouzai, Youssef, Gracie, Renata, De Matos, Vanderlei Pascoal, Gurgel, Helen, Dessay, Nadine
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2510.03725
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author Hallopeau, Thomas
Guérin, Joris
Demagistri, Laurent
Fouzai, Youssef
Gracie, Renata
De Matos, Vanderlei Pascoal
Gurgel, Helen
Dessay, Nadine
author_facet Hallopeau, Thomas
Guérin, Joris
Demagistri, Laurent
Fouzai, Youssef
Gracie, Renata
De Matos, Vanderlei Pascoal
Gurgel, Helen
Dessay, Nadine
contents While deep learning methods for detecting informal settlements have already been developed, they have not yet fully utilized the potential offered by recent pretrained neural networks. We compare two types of pretrained neural networks for detecting the favelas of Rio de Janeiro: 1. Generic networks pretrained on large diverse datasets of unspecific images, 2. A specialized network pretrained on satellite imagery. While the latter is more specific to the target task, the former has been pretrained on significantly more images. Hence, this research investigates whether task specificity or data volume yields superior performance in urban informal settlement detection.
format Preprint
id arxiv_https___arxiv_org_abs_2510_03725
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Mapping Rio de Janeiro's favelas: general-purpose vs. satellite-specific neural networks
Hallopeau, Thomas
Guérin, Joris
Demagistri, Laurent
Fouzai, Youssef
Gracie, Renata
De Matos, Vanderlei Pascoal
Gurgel, Helen
Dessay, Nadine
Computer Vision and Pattern Recognition
Machine Learning
While deep learning methods for detecting informal settlements have already been developed, they have not yet fully utilized the potential offered by recent pretrained neural networks. We compare two types of pretrained neural networks for detecting the favelas of Rio de Janeiro: 1. Generic networks pretrained on large diverse datasets of unspecific images, 2. A specialized network pretrained on satellite imagery. While the latter is more specific to the target task, the former has been pretrained on significantly more images. Hence, this research investigates whether task specificity or data volume yields superior performance in urban informal settlement detection.
title Mapping Rio de Janeiro's favelas: general-purpose vs. satellite-specific neural networks
topic Computer Vision and Pattern Recognition
Machine Learning
url https://arxiv.org/abs/2510.03725