First, similar to how the Transformer works, the Vision Transformer is supervised, meaning the model is trained on a dataset of images and their corresponding labels. Convert the patch into a vector ...

In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

Transformers, first proposed in a Google research paper in 2017, were initially designed for natural language processing (NLP) tasks. Recently, researchers applied transformers to vision applications ...