2026-10-13T22:09:05Zhttps://www.radar-service.eu/oai/OAIHandler10.35097/6m6dm7pfuz930few2026-10-09T11:00:02Zradar4kit
https://dx.doi.org/10.35097/6m6dm7pfuz930few
Krikau, Svea
PVMultiSegNet: Framework for Simultaneous Segmentation of Rooftop and Ground-Mounted Photovoltaics
Karlsruhe Institute of Technology
2025
Engineering
dataset
Software
info:eu-repo/semantics/openAccess
Other
info:eu-repo/semantics/openAccess
https://opensource.org/licenses/MIT
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.
photovoltaic
image processing
remote sensing
renewable energy
https://publikationen.bibliothek.kit.edu/1000184009
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