Medical image segmentation is an important application field of computer vision in medical
image processing. Due to the close location and high similarity of different organs in medical …

Highway merging bottleneck is challenged with serious traffic conflicts between on‐ramp
and mainline vehicles, causing significant capacity drop and drastic speed changes. The …

In the marine environment, there are problems such as complex background and low
illumination, resulting in poor picture quality, and the aggregation of small targets and …

Facial expression recognition (FER) is a widely used technique for emotion recognition. In
recent years, numerous deep convolutional neural network (CNN) models have been …

Multiple object tracking is challenging due to the complex spatiotemporal relationship and
the occlusion of different targets. Most existing methods use separate neural networks to …

Target enhancement is the most important task in a video surveillance system. In order to
improve the accuracy and efficiency of target enhancement, and better deal with the …

Over the past few decades, there has been a lot of advancement in face hallucination (or
super-resolution) technologies, with the position-patch-based locality constrained methods …

A network structure (DRSN‐GAN) is proposed for image motion deblurring that combines a
deep residual shrinkage network (DRSN) with a generative adversarial network (GAN) to …

The tradeoff among spatial, temporal, and spectral resolution of remote sensing (RS) images
due to sensor properties limits the development of RS applications. Most image …

Computerized tomography (CT) is widely used for clinical screening and treatment planning.
In this study, we aimed to reduce X‐ray radiation and achieve high‐quality CT imaging by …