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Creator/Author:
Krikau, Svea https://orcid.org/0009-0000-5723-9627 [Fakultät für Bauingenieur-, Geo- und Umweltwissenschaften (BGU), Karlsruher Institut für Technologie (KIT)]
Contributors:
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Title:
PVMultiSegNet: Framework for Simultaneous Segmentation of Rooftop and Ground-Mounted Photovoltaics
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Description:
(Abstract) 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 IE...

(Technical Remarks) Extract the ZIP folder to obtain the files needed to run PVMultiSegNet. The README file contains instructions for managing the code.
Keywords:
photovoltaic
image processing
remote sensing
renewable energy
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Subject areas:
Engineering
Resource type:
Software
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Status:
Published
Uploaded by:
kitopen
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Archiving date:
2025-08-19
Archive size:
340.5 MB
Archive creator:
kitopen
Archive checksum:
7eb92bfed0c36e6018defd094918158c (MD5)
Embargo period:
2026-02-01