Brain Tumor Classification Using a Hybrid Learning Strategy Integrating GAN-Augmented Neural Networks
A hybrid framework that combines generative adversarial networks (GANs), convolutional neural networks (CNNs), and Vision Transformers (ViTs) for accurate tumor classification demonstrates the potential of advanced DL models to strengthen MRI-based tumor diagnosis and support more reliable clinical decision-making.