Adaptive Input-image Normalization for Solving the Mode Collapse Problem in GAN-based X-ray Images

arXiv:2309.12245v3 Announce Type: replace-cross
Abstract: Biomedical image datasets can be imbalanced due to the rarity of targeted diseases. Generative Adversarial Networks play a key role in addressing this imbalance by enabling the generation of synthetic images to augment datasets. It is important to generate synthetic images that incorporate a diverse range of features to accurately represent the distribution of features present in the training imagery. Furthermore, the absence of diverse features in synthetic images can degrade the performance of machine …

abstract adversarial arxiv augment biomedical cs.cv cs.lg datasets diseases eess.iv enabling gan generate generative generative adversarial networks image image datasets images key networks normalization ray role synthetic type x-ray