Адаптація контексту у задачах класифікації зображень

dc.contributor.advisor	Швай, Надія
dc.contributor.author	Крошин, Олександр
dc.date.accessioned	2022-01-17T21:18:11Z
dc.date.available	2022-01-17T21:18:11Z
dc.date.issued	2021
dc.description.abstract	Rapid developments in the Deep Learning domain in recent years let researchers and practitioners shift their focus from training machine learning models itself to transferring the already-learnt knowledge and applying it in different applications. This paper discusses Domain Adaptation, a subdomain of transfer learning, primarily aimed at applying knowledge from a given source domain to an unknow target one. It discusses various Domain Adaptation settings under the context of Computer Vision, introduces self-ensembling Domain Adaptation methods for semi-supervised learning and illustrates its capabilities with proper experiments. Experiments were implemented with Python 3.6 using libraries pytorch, numpy, pandas, opencv, matplotlib, torch-salad, etc.	uk_UA
dc.identifier.uri	https://ekmair.ukma.edu.ua/handle/123456789/22284
dc.language.iso	en	uk_UA
dc.status	first published	uk_UA
dc.subject	адаптація	uk_UA
dc.subject	класифікація зображень	uk_UA
dc.subject	магістерська робота	uk_UA
dc.title	Адаптація контексту у задачах класифікації зображень	uk_UA
dc.type	Other	uk_UA

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Name:: Kroshyn_Adaptatsiia_kontekstu_u_zadachakh_klasyfikatsii_zobrazhen.pdf
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Format:: Adobe Portable Document Format
Description:: магістерська робота

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