mlsanityData to 14 Oct 2026

Mapping Rio de Janeiro's favelas: general-purpose vs. satellite-specific neural networks

arXiv 2510.03725 ↗First posted 4 Oct 2025cs.CV cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 20 references that are in the map. First posted on arXiv 4 Oct 2025.

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References · 8

  1. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  2. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,403
  3. 2023SpectralGPT: Spectral Remote Sensing Foundation Modelcited by 252
  4. 2023SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagerycited by 205
  5. 2023CROMA: Remote Sensing Representations with Contrastive Radar-Optical Masked Autoencoderscited by 169
  6. 2022Advancing Plain Vision Transformer Towards Remote Sensing Foundation Modelcited by 149
  7. 2022SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observationcited by 84
  8. 2023A Billion-scale Foundation Model for Remote Sensing Imagescited by 62

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