By integrating the information contained in multiple images of the same scene into one
composite image, pixel-level image fusion is recognized as having high significance in a …

Multi-focus image fusion is an effective technique to extend the depth-of-field of optical
lenses by creating an all-in-focus image from a set of partially focused images of the same …

Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …

Deep learning technology has been extensively explored in pattern recognition and image
processing areas. A multi-mode medical image fusion with deep learning will be proposed …

As a popular signal modeling technique, sparse representation (SR) has achieved great
success in image fusion over the last few years with a number of effective algorithms being …

Over past several years, machine learning, or more generally artificial intelligence, has
generated overwhelming research interest and attracted unprecedented public attention. As …

In this letter, a sparse representation (SR) model named convolutional sparsity based
morphological component analysis (CS-MCA) is introduced for pixel-level medical image …

In this work, we propose a deep learning framework for the classification of COVID-19
pneumonia infection from normal chest CT scans. In this regard, a 15-layered convolutional …

The field of medical image reconstruction has seen roughly four types of methods. The first
type tended to be analytical methods, such as filtered backprojection (FBP) for X-ray …

In this paper, we propose a novel deep convolutional neural network to solve the general
multi-modal image restoration (MIR) and multi-modal image fusion (MIF) problems. Different …