Graph-Supported Preparation of GIS Machine Learning Datasets
Data
2023
Autorzy
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
The paper presents an approach to preparing spatial (GIS) datasets
for machine learning models, and using graph structure to materialise and
utilise the results. The presented work is based on the Spatially-Triggered
Graph Transformations (STGT) methodology, previously used for many realworld
applications, e.g. in the area of smart cities. A workflow using OSM
data is presented, aimed at improving the granularity and semantic annotation
of map features.
Opis
Słowa kluczowe
graph transformations, ML, classification, GIS, smart cities, transformacje grafów, ML, klasyfikacja, ML, inteligentne miasta
Cytowanie
Ernst S., Graph-Supported Preparation of GIS Machine Learning Datasets. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 107-112, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.15.