3 citations · 5 across the 3 of their papers we have counts for
3 papers
Implicit neural representation for change detection
Peter Naylor, Diego Di Carlo, Arianna Traviglia +2
Identifying changes in a pair of 3D aerial LiDAR point clouds, obtained during two distinct time periods over the same geographic region presents a significant challenge due to the…
Optimal Transport for Change Detection on LiDAR Point Clouds
Marco Fiorucci, Peter Naylor, Makoto Yamada
Unsupervised change detection between airborne LiDAR data points, taken at separate times over the same location, can be difficult due to unmatching spatial support and noise from…
Scale dependant layer for self-supervised nuclei encoding
Peter Naylor, Yao-Hung Hubert Tsai, Marick Laé +1
Recent developments in self-supervised learning give us the possibility to further reduce human intervention in multi-step pipelines where the focus evolves around particular objec…