107 citations · 112 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
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…
Benchmarking Individual Tree Mapping with Sub-meter Imagery
Dimitri Gominski, Ankit Kariryaa, Martin Brandt +4
There is a rising interest in mapping trees using satellite or aerial imagery, but there is no standardized evaluation protocol for comparing and enhancing methods. In dense canopy…
MaskIt: Masking for efficient utilization of incomplete public datasets for training deep learning models
Ankit Kariryaa
A major challenge in training deep learning models is the lack of high quality and complete datasets. In the paper, we present a masking approach for training deep learning models…