PVMultiSegNet: Framework for Simultaneous Segmentation of Rooftop and Ground-Mounted Photovoltaics

DOI

A deep learning framework for simultaneous segmentation of rooftop and ground-mounted photovoltaic (PV) systems using multispectral remote sensing data.

Extract the ZIP folder to obtain the files needed to run PVMultiSegNet. The README file contains instructions for managing the code.

Identifier
DOI https://doi.org/10.35097/6m6dm7pfuz930few
Related Identifier IsIdenticalTo https://publikationen.bibliothek.kit.edu/1000184009
Metadata Access https://www.radar-service.eu/oai/OAIHandler?verb=GetRecord&metadataPrefix=datacite&identifier=10.35097/6m6dm7pfuz930few
Provenance
Creator Krikau, Svea ORCID logo
Publisher Karlsruhe Institute of Technology
Contributor RADAR
Publication Year 2025
Rights Open Access; Other; info:eu-repo/semantics/openAccess
OpenAccess true
Representation
Resource Type Software
Format application/x-tar
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences