2 papers
cs.CV2024
Early Stopping Criteria for Training Generative Adversarial Networks in Biomedical Imaging
Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly
Generative Adversarial Networks (GANs) have high computational costs to train their complex architectures. Throughout the training process, GANs' output is analyzed qualitatively b…
eess.IV2024
Adaptive Input-image Normalization for Solving the Mode Collapse Problem in GAN-based X-ray Images
Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly
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 gen…