Abstract Transformers are Deep Neural Networks (DNN) that utilize a self-attention
mechanism to capture contextual relationships within sequential data. Unlike traditional …

Transformers have been widely used in many computer vision challenges and have shown
the capability of producing better results than convolutional neural networks (CNNs). Taking …

Vision transformers have become popular as a possible substitute to convolutional neural
networks (CNNs) for a variety of computer vision applications. These transformers, with their …

Accurate lesion segmentation is a critical technology basis for the treatment and prognosis
of stroke. Stroke lesion segmentation suffers from complex background and noise interferes …

In recent years, denoising diffusion models have achieved remarkable success in
generating pixel-level representations with semantic values for image generation modeling …