Search Results for author:
Found 2 papers, 2 papers with code
A Semantic Segmentation-guided Approach for Ground-to-Aerial Image Matching
Nowadays the accurate geo-localization of ground-view images has an important role across domains as diverse as journalism, forensics analysis, transports, and Earth Observation.
Learning from Unlabelled Data with Transformers: Domain Adaptation for Semantic Segmentation of High Resolution Aerial Images
In this paper, we develop a new model for semantic segmentation of unlabelled images, the Non-annotated Earth Observation Semantic Segmentation (NEOS) model.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
