The Evolution of Vision Transformers: A Multi‐Dimensional Analysis of Architectural Innovation and Application Domains
The rapid evolution of deep learning has positioned Vision Transformers (ViTs) as a powerful alternative to convolutional neural networks (CNNs) in computer vision. By leveraging self‐attention to model global dependencies, ViTs achieve state‐of‐the‐art performance across tasks such as image classification and segmenta...