175 citations · 469 across the 6 of their papers we have counts for
5 papers · 1 filter
Mapping Vulnerable Populations with AI
Benjamin Kellenberger, John E. Vargas-Muñoz, Devis Tuia +6
Humanitarian actions require accurate information to efficiently delegate support operations. Such information can be maps of building footprints, building functions, and populatio…
Deploying machine learning to assist digital humanitarians: making image annotation in OpenStreetMap more efficient
John E. Vargas-Muñoz, Devis Tuia, Alexandre X. Falcão
Locating populations in rural areas of developing countries has attracted the attention of humanitarian mapping projects since it is important to plan actions that affect vulnerabl…
OpenStreetMap: Challenges and Opportunities in Machine Learning and Remote Sensing
John Vargas, Shivangi Srivastava, Devis Tuia +1
OpenStreetMap (OSM) is a community-based, freely available, editable map service that was created as an alternative to authoritative ones. Given that it is edited mainly by volunte…
Understanding urban landuse from the above and ground perspectives: a deep learning, multimodal solution
Shivangi Srivastava, John E. Vargas-Muñoz, Devis Tuia
Landuse characterization is important for urban planning. It is traditionally performed with field surveys or manual photo interpretation, two practices that are time-consuming and…
Correcting rural building annotations in OpenStreetMap using convolutional neural networks
John E. Vargas-Muñoz, Sylvain Lobry, Alexandre X. Falcão +1
Rural building mapping is paramount to support demographic studies and plan actions in response to crisis that affect those areas. Rural building annotations exist in OpenStreetMap…