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Information × Registration Number 2123U011183, Article popup.category Препринт Title Research of Data Augmentation Approaches for Enhancing Classification Model Performance (AI translated) popup.author Vey BohdanVey Bohdan popup.publication 01-01-2023 popup.source_user Український католицький університет popup.source https://hdl.handle.net/20.500.14570/4385 popup.publisher Description After a significant improvement in the computational powers of modern comput- ers, the models became larger, and their accuracy increased. However, due to a high amount of parameters, modern neural networks also need much bigger datasets for efficient usage. Augmentation partly solves this problem, but the most up-to- date augmentation still doesn’t change the image patterns. We propose a new way of augmentation by using inpainting models to change the image’s nature. Then we compare model performance by using traditional augmentation and GANAug- mentation. The second part of this study will use Test Time Augmentation(TTA) to improve model performance for data which come from another source. popup.nrat_date 2025-11-05 Close