The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Transformers have dominated the field of natural language processing and have recently
made an impact in the area of computer vision. In the field of medical image analysis …

Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …

Generative adversarial models with convolutional neural network (CNN) backbones have
recently been established as state-of-the-art in numerous medical image synthesis tasks …

Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …

In this paper, a multi-scale visual transformer model, referred as GasHis-Transformer, is
proposed for Gastric Histopathological Image Detection (GHID), which enables the …

Medical ultrasound (US) imaging has become a prominent modality for breast cancer
imaging due to its ease of use, low cost, and safety. In the past decade, convolutional neural …

The automated classification of brain tumors plays an important role in supporting
radiologists in decision making. Recently, vision transformer (ViT)-based deep neural …