Zobrazeno 1 - 10 of 784 pro vyhledávání: '"Arghandeh, R."'
1
Akademický článek
Transformer-based land use and land cover classification with explainability using satellite imagery.
Autor: Khan M; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway. mehakkhan3@hotmail.com., Hanan A; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway., Kenzhebay M; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway., Gazzea M; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway., Arghandeh R; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway. reza.arghandeh@hvl.no.
Publikováno v: Scientific reports [Sci Rep] 2024 Jul 20; Vol. 14 (1), pp. 16744. Date of Electronic Publication: 2024 Jul 20.
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2
AN END-TO-END DEEP LEARNING WORKFLOW FOR BUILDING SEGMENTATION, BOUNDARY REGULARIZATION AND VECTORIZATION OF BUILDING FOOTPRINTS
Autor: Šanca, S., Jyhne, S., Gazzea, M., Arghandeh, R.
Automatic building footprint extraction from remote sensing imagery is a widely used method, with deep learning techniques being particularly effective. However, deep learning approaches still require additional post-processing steps due to pixel-wis
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=copernicuspu::65004bf673ad57bcf03afd67514bd475
https://isprs-archives.copernicus.org/articles/XLVIII-4-W7-2023/169/2023/
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3
Akademický článek
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4
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5
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6
Akademický článek
Short-term inflow forecasting in a dam-regulated river in Southwest Norway using causal variational mode decomposition.
Autor: Yousefi M; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Science, Bergen, Norway. Mojtaba.yousefi@Hvl.no., Wang J; Department of Electric Power Engineering, Norwegian University of Science and Technology, Trondheim, Norway., Fandrem Høivik Ø; Lyse Produksjon AS, Stavanger, Norway., Rajasekharan J; Department of Electric Power Engineering, Norwegian University of Science and Technology, Trondheim, Norway., Hubert Wierling A; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Science, Bergen, Norway., Farahmand H; Department of Electric Power Engineering, Norwegian University of Science and Technology, Trondheim, Norway., Arghandeh R; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Science, Bergen, Norway.
Publikováno v: Scientific reports [Sci Rep] 2023 Apr 29; Vol. 13 (1), pp. 7016. Date of Electronic Publication: 2023 Apr 29.
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7
Akademický článek
Traffic monitoring system design considering multi-hazard disaster risks.
Autor: Gazzea M; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5063, Bergen, Norway. mgaz@hvl.no., Miraki A; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5063, Bergen, Norway., Alisan O; Department of Civil and Environmental Engineering, Florida A & M University-Florida State University College of Engineering, Tallahassee, 32310, USA., Kuglitsch MM; Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, 10587, Berlin, Germany., Pelivan I; Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, 10587, Berlin, Germany., Ozguven EE; Department of Civil and Environmental Engineering, Florida A & M University-Florida State University College of Engineering, Tallahassee, 32310, USA., Arghandeh R; Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5063, Bergen, Norway.
Publikováno v: Scientific reports [Sci Rep] 2023 Mar 25; Vol. 13 (1), pp. 4883. Date of Electronic Publication: 2023 Mar 25.
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8
Akademický článek
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9
Deep learning for power system data analysis
Autor: Mocanu, Elena, Nguyen, Phuong H., Gibescu, Madeleine, Arghandeh, R., Zhou, Y.
Publikováno v: Big data application in power systems, 125-158
STARTPAGE=125;ENDPAGE=158;TITLE=Big data application in power systems
Chapter Overview Unprecedented high volumes of data are available in the smart grid context, facilitated by the growth of home energy management systems and advanced metering infrastructure. In order to automatically extract knowledge from, and take
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::03241cbc858cc6b3e7af920a565a4a13
https://research.tue.nl/nl/publications/8cffb666-3c41-4ac8-979e-678abd0c262e
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10
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