Computer personnel research - Issues and progress in the 60's
David B. Mayer, Ashford W. Stalnaker
ACM SIGMIS CPR 1967
The growing amount of openly available, meter-scale geospatial vertical aerial imagery and the need of the OpenStreetMap (OSM) project for continuous updates bring the opportunity to use the former to help with the latter, e.g., by leveraging the latest remote sensing data in combination with state-of-the-art computer vision methods to assist the OSM community in labeling work. This article reports our progress to utilize artificial neural networks (ANN) for change detection of OSM data to update the map. Furthermore, we aim at identifying geospatial regions where mappers need to focus on completing the global OSM dataset. Our approach is technically backed by the big geospatial data platform Physical Analytics Integrated Repository and Services (PAIRS). We employ supervised training of deep ANNs from vertical aerial imagery to segment scenes based on OSM map tiles to evaluate the technique quantitatively and qualitatively.
David B. Mayer, Ashford W. Stalnaker
ACM SIGMIS CPR 1967
Cen Rao, Alexei Gritai, et al.
ICCV 2003
Sudeep Sarkar, Kim L. Boyer
Computer Vision and Image Understanding
Harman Singh, Poorva Garg, et al.
NeurIPS 2022