Visual question-answering (QA) helps users interpret complex visual information, making it easier and faster to gain insights also from maps and geospatial data in a variety of contexts. This project aims to create an open dataset tailored for thematic map-based QA systems, accompanied by a baseline model to demonstrate its usage. By compiling map images annotated with question-answer pairs, the dataset will enable Artificial Intelligence (AI) models to extract and interpret geographic and information from maps. The deliverables will include a curated dataset, a baseline model, documentation, and an evaluation report, all of which will be released under a permissive license to support further research on the topic.
| Koukouraki, Eftychia |
| Koukouraki, Eftychia |
NFDI Consortium Earth System Sciences (NFDI4Earth) Duration: 01/01/2022 - 30/09/2026 Funded by: DFG - National Research Data Infrastructure Type of project: DFG-joint project hosted outside University of Münster |