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Cравнительный анализ Ð¿Ð¾Ð´Ñ Ð¾Ð´Ð¾Ð² к генерации Ð´Ð°Ð½Ð½Ñ‹Ñ Ð¿Ñ€Ð¸ обработке изображений в случае несбалансированности классов

выпускная квалификационная работа бакалавра

Cравнительный анализ Ð¿Ð¾Ð´Ñ Ð¾Ð´Ð¾Ð² к генерации Ð´Ð°Ð½Ð½Ñ‹Ñ Ð¿Ñ€Ð¸ обработке изображений в случае несбалансированности классов

Abstract

В данной работе были рассмотрены основные особенности, связанные с работой над несбалансированными данными, и основные проблемы при классификации изображений. Разобраны принципы работы модификаций генеративно-состязательных сетей и произведён сравнительный анализ с использованием нескольких метрик их работы над небалансированными классами изображений.

In this paper, the main features associated with working on unbalanced data and the main problems in image classification were considered. The principles of operation of modifications of generative-adversarial networks are analyzed and a comparative analysis is made using several metrics of their work on unbalanced classes of images.

Keywords

автоэнкодер, autoencoder, class imbalance, generative adversarial network, несбалансированность классов, генеративно-состязательная сеть

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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