Khushvir Singh

Hybrid Deep Learning Architecture Integrating ConvNeXtV2, Swin Transformer, and Convolutional Block Attention Module for Enhanced Multiclass Brain Tumor Classification in Magnetic Resonance Imaging

Overall, fusing convolutional and transformer features with attention refinement markedly enhances classification performance and achieves 95.45% accuracy versus RDXNet and ResNet50, with gains across all metrics.