Image restoration (IR) has been an indispensable and challenging task in the low-level
vision field, which strives to improve the subjective quality of images distorted by various …

Medical imaging methods, such as CT scans, MRI scans, X-rays, and ultrasound imaging,
are widely used for diagnosis in the healthcare domain. However, these methods are often …

The Vision Transformer (ViT) architecture has been remarkably successful in image
restoration. For a while, Convolutional Neural Networks (CNN) predominated in most …

The intelligent detection process for industrial anomalies employs artificial intelligence
methods to classify images that deviate from a normal appearance. Traditional convolutional …

The accurate diagnosis of the compound fault of industrial robots can be highly beneficial to
maintenance management. In the actual noisy working environment of industrial robots, the …

Semantic communication is expected to be one of the cores of next-generation AI-based
communications. One of the possibilities offered by semantic communication is the capability …

As a special type of transformer, vision transformers (ViTs) can be used for various computer
vision (CV) applications. Convolutional neural networks (CNNs) have several potential …

Low-dose computed tomography (LDCT) can significantly reduce the damage of X-ray to the
human body, but the reduction of CT dose will produce images with severe noise and …

Image restoration is one of the most important computer vision tasks, aiming at recovering
high-quality images from degraded or low-quality observations. The restoration methods …

Accurate object tracking in low-light environments is crucial, particularly in surveillance,
ethology applications, and biometric recognition systems. However, achieving this is …