ViT (Vision Transformer)

The Vision Transformer (ViT) is a machine learning model that processes images by breaking them into smaller pieces called patches, similar to tiles on a floor. It then analyzes these patches collectively, using a system inspired by language models to understand the overall image. Unlike traditional methods that rely on step-by-step feature detection, ViT treats the image like a sequence of tokens (patches) and uses attention mechanisms to focus on important parts. This approach allows ViT to effectively recognize objects and patterns in images, often achieving performance comparable to or better than older methods.