2026-06-05T00:26:09Zhttps://www.radar-service.eu/oai/OAIHandler10.35097/6m6dm7pfuz930few2026-02-10T09:42:54Zradar4kit
10.35097/6m6dm7pfuz930few
Krikau, Svea
Svea
Krikau
0009-0000-5723-9627
Fakultät für Bauingenieur-, Geo- und Umweltwissenschaften (BGU), Karlsruher Institut für Technologie (KIT)
PVMultiSegNet: Framework for Simultaneous Segmentation of Rooftop and Ground-Mounted Photovoltaics
Karlsruhe Institute of Technology
2025
2025
Engineering
photovoltaic
image processing
remote sensing
renewable energy
Open Access
Other
Krikau, Svea
0009-0000-5723-9627
A deep learning framework for simultaneous segmentation of rooftop and ground-mounted photovoltaic (PV) systems using multispectral remote sensing data.
The code relates to the publication: S. Krikau and S. Keller, "Deep Learning Framework for Multi-Class Segmentation of Photovoltaic Systems," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2025.3640268.
Extract the ZIP folder to obtain the files needed to run PVMultiSegNet. The README file contains instructions for managing the code.
https://publikationen.bibliothek.kit.edu/1000184009
340,5 MB
application/x-tar