1 citations · 1 across the 3 of their papers we have counts for
5 papers
Align and Segment: Unsupervised Learning for Building Segmentation From Misaligned Labels
Venkanna Babu Guthula, Oswin Krause, Dimitri Gominski +5
Supervised learning for image segmentation typically requires spatially aligned image and label sets. When images and labels originate from different sources, the pairing may be mi…
Multimodal classification of forest biodiversity potential from 2D orthophotos and 3D airborne laser scanning point clouds
Simon B. Jensen, Stefan Oehmcke, Andreas Møgelmose +4
Assessment of forest biodiversity is crucial for ecosystem management and conservation. While traditional field surveys provide high-quality assessments, they are labor-intensive a…
Nacala-Roof-Material: Drone Imagery for Roof Detection, Classification, and Segmentation to Support Mosquito-borne Disease Risk Assessment
Venkanna Babu Guthula, Stefan Oehmcke, Remigio Chilaule +5
As low-quality housing and in particular certain roof characteristics are associated with an increased risk of malaria, classification of roof types based on remote sensing imagery…
MMEarth: Exploring Multi-Modal Pretext Tasks For Geospatial Representation Learning
Vishal Nedungadi, Ankit Kariryaa, Stefan Oehmcke +3
The volume of unlabelled Earth observation (EO) data is huge, but many important applications lack labelled training data. However, EO data offers the unique opportunity to pair da…
Predicting urban tree cover from incomplete point labels and limited background information
Hui Zhang, Ankit Kariryaa, Venkanna Babu Guthula +2
Trees inside cities are important for the urban microclimate, contributing positively to the physical and mental health of the urban dwellers. Despite their importance, often only…