436 citations · 461 across the 4 of their papers we have counts for
4 papers
Channel Boosted CNN-Transformer-based Multi-Level and Multi-Scale Nuclei Segmentation
Zunaira Rauf, Abdul Rehman Khan, Asifullah Khan
Accurate nuclei segmentation is an essential foundation for various applications in computational pathology, including cancer diagnosis and treatment planning. Even slight variatio…
A Recent Survey of Vision Transformers for Medical Image Segmentation
Asifullah Khan, Zunaira Rauf, Abdul Rehman Khan +13
Medical image segmentation plays a crucial role in various healthcare applications, enabling accurate diagnosis, treatment planning, and disease monitoring. Traditionally, convolut…
A survey of the Vision Transformers and their CNN-Transformer based Variants
Asifullah Khan, Zunaira Rauf, Anabia Sohail +4
Vision transformers have become popular as a possible substitute to convolutional neural networks (CNNs) for a variety of computer vision applications. These transformers, with the…
CB-HVTNet: A channel-boosted hybrid vision transformer network for lymphocyte assessment in histopathological images
Momina Liaqat Ali, Zunaira Rauf, Asifullah Khan +3
Transformers, due to their ability to learn long range dependencies, have overcome the shortcomings of convolutional neural networks (CNNs) for global perspective learning. Therefo…