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Examining the Portability of Deep Learning Runtime Optimization Methods

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dc.contributor.authorTavukçu, Muhammet Alpaslan
dc.contributor.authorYılmazer-Metin, Ayşe
dc.contributor.ituauthorTAVUKÇU, MUHAMMET ALPASLAN
dc.contributor.ituauthorYılmazer Metin, Ayşe
dc.date.accessioned2026-01-24T11:54:17Z
dc.date.issued2025-06-25
dc.description.urihttps://doi.org/10.1109/siu66497.2025.11111816
dc.identifier.doi10.1109/siu66497.2025.11111816
dc.identifier.endpage4
dc.identifier.openairedoi_________::af1e3faecc94c60befc8c9bcbe48cdb9
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11527/31405
dc.publisherIEEE
dc.relation.ispartof2025 33rd Signal Processing and Communications Applications Conference (SIU)
dc.rightsCLOSED
dc.titleExamining the Portability of Deep Learning Runtime Optimization Methods
dc.typeArticle
dspace.entity.typePublication
person.identifier.orcid0000-0003-4502-7365

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