Image super-resolution (SR) is one of the vital image processing methods that improve the
resolution of an image in the field of computer vision. In the last two decades, significant …

Deep convolutional neural networks can effectively improve the performance of single-
image super-resolution reconstruction. Deep networks tend to achieve better performance …

This paper presents a novel facial expression recognition network, called Distract your
Attention Network (DAN). Our method is based on two key observations in biological visual …

In order to solve the issue mismatching and structure disconnecting in exemplar-based
image inpainting, an image completion algorithm based on improved total variation …

Most RUL prediction methods can only extract single-scale features, ignoring significant
details at other scales and layers. These methods are all constructed using one type of …

Abstract Recently, super-resolution (SR) techniques based on deep learning have taken
more and more attention, aiming to improve the images and videos resolutions. Most of the …

High-quality magnetic resonance imaging (MRI) affords clear body tissue structure for
reliable diagnosing. However, there is a principal problem of the trade-off between …

Speech emotion recognition is the crucial stream in emotional computing and also create
few issues owing to its complication in processing. The efficiency of the acoustic methods …

Although time series prediction is widely used to estimate the future state of complex
systems in various industries, accurate, interpretable and generalizable methods are still …

Motivation: Open-source organizations use issues to collect user feedback, software bugs,
and feature requests in GitHub. Many issues do not have labels, which makes labeling time …