Deep learning techniques have received much attention in the area of image denoising.
However, there are substantial differences in the various types of deep learning methods …

Artificial vision has often been described as one of the key remaining challenges to be
solved before machines can act intelligently. Recent developments in a branch of machine …

Due to strong learning ability, convolutional neural networks (CNNs) have been developed
in image denoising. However, convolutional operations may change original distributions of …

Deep convolutional neural networks (CNNs) have attracted considerable interest in low-
level computer vision. Researches are usually devoted to improving the performance via …

Deep convolutional neural networks (CNNs) have attracted great attention in the field of
image denoising. However, there are two drawbacks:(1) it is very difficult to train a deeper …

Deep convolutional neural networks (CNNs) with strong learning abilities have been used in
the field of image denoising. However, some CNNs depend on a single deep network to …

Non-local self-similarity in natural images has been verified to be an effective prior for image
restoration. However, most existing deep non-local methods assign a fixed number of …

During the past decade, deep learning is one of the essential breakthroughs made in
artificial intelligence. In particular, it has achieved great success in image processing …

In recent years, convolutional neural networks have achieved considerable success in
different computer vision tasks, including image denoising. In this work, we present a …

Deep Learning, and Deep Neural Networks in particular, have established themselves as
the new norm in signal and data processing, achieving state-of-the-art performance in …