Featured by a bottleneck structure, autoencoder (AE) and its variants have been largely applied in various medical image analysis tasks, such as segmentation, reconstruction and de-noising. Despite of ...

Variational AutoEncoders (VAE) have grown in popularity due to their scalability and computational efficiency. It is widely used in voice modeling, clustering, and data augmentation applications. This ...

Abstract: Due to severe information loss of low-resolution images, the development of single-image super-resolution methods is limited. Recently, the reference-based image super-resolution methods, ...

This paper focuses on improving the spatial resolution of the hyperspectral image (HSI) by taking the prior information into consideration. In recent years, single HSI super-resolution methods based ...

Single-molecule super-resolution microscopy (SMLM) techniques like dSTORM can reveal biological structures down to the nanometer scale. The achievable resolution is not only defined by the ...

Abstract: In this paper, we propose a novel reference based image super-resolution approach via Variational AutoEncoder (RefVAE). Existing state-of-the-art methods mainly focus on single image ...