The linear inverse problem is fundamental to the development of various scientific areas.
Innumerable attempts have been carried out to solve different variants of the linear inverse …

Image restoration is a challenging ill-posed problem which also has been a long-standing
issue. In the past few years, the convolution neural networks (CNNs) almost dominated the …

Single image super resolution (SISR) is an important research content in the field of
computer vision and image processing. With the rapid development of deep neural …

Intrusion Detection systems are important tools in preventing malicious traffic from
penetrating into networks and systems. Recently, Intrusion Detection Systems are rapidly …

Lung nodule classification plays an important role in diagnosis of lung cancer which is
essential to patients' survival. However, because the number of lung CT images in current …

Image restoration is a low-level vision task which is to restore degraded images to noise-free
images. With the success of deep neural networks, the convolutional neural networks …

With the gradually increasing demand for high-resolution images, image super-resolution
(SR) technology has become more and more important in our daily life. In general, high …

Common cameras cannot capture high quality image in the night or extreme weather
conditions that without enough light, while thermal infrared (TIR) cameras are not limited in …

In recent years, deep-learning-based single image super-resolution reconstruction has
achieved good performance. However, most existing methods pursue a high peak signal-to …

In this work, we presented a novel clothing brand logo prediction method which is rooted on
a dense-block based deep convolutional neural network for brand logo detection and …