S. H. Ali

HierTAC-Net: a robust and explainable hierarchical attention network for multi-configuration gastrointestinal endoscopic image classification

HierTAC-Net is proposed, a six-stage convolutional classifier that combines inverted residual blocks, triple attention at three resolution levels, and ConvNeXt-style refinement that is suitable for real-time deployment and remains stable under common artifacts and across two clinical collections.