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Self-supervised Variational Autoencoder for Unsupervised Object Counting from Very High-Resolution Satellite Imagery: Applications in Dwelling Extraction in FDP Settlement Areas

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Article number4701018
Pages (from-to)1-18
Number of pages18
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume62
DOIs
Publication statusPublished - 2024

Bibliographical note

Publisher Copyright:
© 1980-2012 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 1 - No Poverty
    SDG 1 No Poverty
  2. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  3. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  4. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Annotations
  • Anomaly
  • Anomaly detection
  • cutPaste
  • Dwelling counting
  • Image reconstruction
  • latent space conditioning
  • localization
  • Location awareness
  • Satellite images
  • self-supervision
  • Task analysis
  • Training
  • unsupervised learning
  • Variational Autoencoder

Fields of Science and Technology Classification 2012

  • 107 Other Natural Sciences

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