0000000000359426
AUTHOR
Sander Jyhne
MapAI: Precision in BuildingSegmentation
MapAI: Precision in Building Segmentation is a competition arranged with the Norwegian Artificial Intelligence Research Consortium (NORA) in collaboration with Centre for Artificial Intelligence Research at the University of Agder (CAIR), the Norwegian Mapping Authority, AI:Hub, Norkart, and the Danish Agency for Data Supply and Infrastructure. The competition will be held in the fall of 2022. It will be concluded at the Northern Lights Deep Learning conference focusing on the segmentation of buildings using aerial images and laser data. We propose two different tasks to segment buildings, where the first task can only utilize aerial images, while the second must use laser data (LiDAR) with…
DET: Data Enhancement Technique for Aerial Images
Deep learning and computer vision are two thriving research areas within machine learning. In recent years, as the available computing power has grown, it has led to the possibility of combining the approaches, achieving state-of-the-art results. An area of research that has greatly benefited from this development is building detection. Although the algorithms produce satisfactory results, there are still many limitations. One significant problem is the quality and edge sharpness of the segmentation masks, which are not up to the standard required by the mapping industry. The predicted mask boundaries need to be sharper and more precise to have practical use in map production. This thesis i…