11 citations · 37 across the 6 of their papers we have counts for
6 papers
Lidar-based Norwegian tree species detection using deep learning
Martijn Vermeer, Jacob Alexander Hay, David Völgyes +3
Background: The mapping of tree species within Norwegian forests is a time-consuming process, involving forest associations relying on manual labeling by experts. The process can i…
Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations
Anuja Vats, David Völgyes, Martijn Vermeer +4
Estimating building footprint maps from geospatial data is of paramount importance in urban planning, development, disaster management, and various other applications. Deep learnin…
The Nature of Faint Fuzzies from the Kinematics of NGC1023
A. L. Chies-Santos, A. Cortesi, D. S. M. Fantin +3
Faint fuzzies are metal-rich apparently-old star clusters with unusually large radii (7-15 pc), found mostly in S0 galaxies, whose source remain obscure. To identify their origins,…
Estimation of distances within the Milky Way using tidal streams
Daniele S. M. Fantin
During the past 20 years, numerous stellar streams have been discovered in both the Milky Way and the Local Group. These streams have been tidally torn from orbiting systems, which…
Ultra-fine dark matter structure in the Solar neighbourhood
Daniele S. M. Fantin, Anne M. Green, Michael R. Merrifield
The direct detection of dark matter on Earth depends crucially on its density and its velocity distribution on a milliparsec scale. Conventional N-body simulations are unable to ac…
Modelling ultra-fine structure in dark matter halos
Daniele S. M. Fantin, Michael R. Merrifield, Anne M. Green
Various laboratory-based experiments are underway attempting to detect dark matter directly. The event rates and detailed signals expected in these experiments depend on the dark m…