The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks
(CNNs) in creating artistic imagery by separating and recombining image content and style …

Radiomics converts medical images into mineable data via a high-throughput extraction of
quantitative features used for clinical decision support. However, these radiomic features are …

Although existing artistic style transfer methods have achieved significant improvement with
deep neural networks, they still suffer from artifacts such as disharmonious colors and …

Universal style transfer retains styles from reference images in content images. While
existing methods have achieved state-of-the-art style transfer performance, they are not …

In this paper, we propose a solution to transforming photos of real-world scenes into cartoon
style images, which is valuable and challenging in computer vision and computer graphics …

Single image super-resolution (SISR) deals with a fundamental problem of upsampling a
low-resolution (LR) image to its high-resolution (HR) version. Last few years have witnessed …

Edge detection technology aims to identify and extract the boundary information of image
pixel mutation, which is a research hotspot in the field of computer vision. This technology …

We present a new image editing method, particularly effective for sharpening major edges
by increasing the steepness of transition while eliminating a manageable degree of low …

In this paper, we propose a novel explicit image filter called guided filter. Derived from a
local linear model, the guided filter computes the filtering output by considering the content …

Ride-hailing platforms (eg, Uber and Didi Chuxing) have become increasingly popular in
recent years. Efficiency has always been an important metric for such platforms. However …