Search Results for author:
Found 3 papers, 1 papers with code
Distortions in Judged Spatial Relations in Large Language Models: The Dawn of Natural Language Geographic Data?
We discuss the potential of text-based data representing geographic relationships directly to improve the spatial reasoning capabilities of LLMs.
Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks
Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on individual urban environments (e. g., single cities or regions).
Semi-supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation
In this work, we propose a semi-supervised learning (SSL) method of automatically estimating building height from Mapillary SVI and OSM data to generate low-cost and open-source 3D city modeling in LoD1.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
