Vision Transformer Architectures for Next-Generation Image Classification: Attention-Driven Visual Understanding
Vision Transformer (ViT) architectures have emerged as powerful alternatives to conventional convolutional neural networks for image classification because they model long-range visual dependencies through self-attention. This paper presents a software-based image classification framework that uses a pre-trained ViT-Ba...