4 code implementations • 29 Jun 2021 • Vajira Thambawita, Pegah Salehi, Sajad Amouei Sheshkal, Steven A. Hicks, Hugo L. Hammer, Sravanthi Parasa, Thomas de Lange, Pål Halvorsen, Michael A. Riegler
The pipeline is evaluated using qualitative and quantitative comparisons between real and synthetic data to show that the style transfer technique used in our pipeline significantly improves the quality of the generated data and our method is better than other state-of-the-art GANs to prepare synthetic images when the size of training datasets are limited.
1 code implementation • 21 Aug 2020 • Sajad Amouei Sheshkal, Kazim Fouladi-Ghaleh, Hossein Aghababa
The advantages of verification loss were used in the network learning.