National Repository of Grey Literature 1 records found  Search took 0.01 seconds. 
Dataset augmentation with style transfer methods
Wolny, Michał ; Ligocki, Adam (referee) ; Kratochvíla, Lukáš (advisor)
This bachelor's thesis focuses on the research of dataset augmentation and style transfer methods. From the range of available style transfer algorithms, three very different methods were selected, implemented and then experimentally used for dataset augmentation. The effectiveness of augmentation using these methods was verified by performing a statistical analysis of each newly created dataset compared to the original, unmodified dataset. The results of the analysis provide important information about changes in statistical characteristics such as entropy, mean, median, variance, and standard deviation. This information helped to evaluate the effectiveness and impact of the augmentation methods used on the augmented dataset and provide evidence of their potential.

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