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Efektivnost hlubokých konvolučních neuronových sítí na elementární klasifikační úloze / Efficiency of deep convolutional neural networks on an elementary classification task

In this thesis deep convolutional neural networks models and feature descriptor models are compared. Feature descriptors are paired with suitable chosen classifier. These models are a part of machine learning therefore machine learning types are described in this thesis. Further these chosen models are described, and their basics and problems are explained. Hardware and software used for tests is listed and then test results and results summary is listed. Then comparison based on the validation accuracy and training time of these said models is done.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:442831
Date January 2021
CreatorsPrax, Jan
ContributorsDobrovský, Ladislav, Škrabánek, Pavel
PublisherVysoké učení technické v Brně. Fakulta strojního inženýrství
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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