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Leveraging GANs for data scarcity of COVID-19: Beyond the hype
These recommendations might be useful to improve acceptability for the GAN-based approaches for data augmentation as GANs for data augmentation are increasingly becoming popular in the AI and medical imaging research community.
R2U++: A Multiscale Recurrent Residual U-Net with Dense Skip Connections for Medical Image Segmentation
The problem can be ascribed to its simple feature extracting blocks: encoder/decoder, and the semantic gap between encoder and decoder.
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