Comparison of Performance of Optimized HSI CNN models on Desktop and Embedded Platforms

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dc.contributor.authorČech Jiřícs
dc.contributor.authorRozkovec Martincs
dc.date.accessioned2022-01-29T19:04:29Z
dc.date.available04-14-2021en
dc.date.available2022-01-29T19:04:29Z
dc.date.issued2021cs
dc.format.extent4cs
dc.identifier.doi10.23919/AE51540.2021.9542900
dc.identifier.isbn978-802610972-3cs
dc.identifier.issn1803-7232cs
dc.identifier.urihttps://dspace.tul.cz/handle/15240/162295
dc.language.isoengcs
dc.publisherIEEEcs
dc.publisher.cityPilsen, Czech Republiccs
dc.relation.ispartofInternational Conference on Applied Electronicsen
dc.relation.ispartofseries1cs
dc.relation.urihttps://ieeexplore.ieee.org/document/9542900cs
dc.subjectHyperspectral imagingcs
dc.subjectNeural networkscs
dc.subjectXilinx FPGAcs
dc.subjectVitis AIcs
dc.subjectDPUcs
dc.titleComparison of Performance of Optimized HSI CNN models on Desktop and Embedded Platformsen
dc.titleComparison of Performance of Optimized HSI CNN models on Desktop and Embedded Platformscs
local.event.locationPilsenen
local.identifier.publikace8992
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