131 citations · 302 across the 10 of their papers we have counts for
10 papers
A fast and flexible algorithm for microstructure reconstruction combining simulated annealing and deep learning
Zhenchuan Ma, Xiaohai He, Pengcheng Yan +2
The microstructure analyses of porous media have considerable research value for the study of macroscopic properties. As the premise of conducting these analyses, the accurate reco…
Multiscale reconstruction of porous media based on multiple dictionaries learning
Pengcheng Yan, Qizhi Teng, Xiaohai He +2
Digital modeling of the microstructure is important for studying the physical and transport properties of porous media. Multiscale modeling for porous media can accurately characte…
Real-World Single Image Super-Resolution: A Brief Review
Honggang Chen, Xiaohai He, Linbo Qing +3
Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR) image from a low-resolution (LR) observation, has been an active research topic in the area o…
FTGAN: A Fully-trained Generative Adversarial Networks for Text to Face Generation
Xiang Chen, Lingbo Qing, Xiaohai He +2
As a sub-domain of text-to-image synthesis, text-to-face generation has huge potentials in public safety domain. With lack of dataset, there are almost no related research focusing…
Accurate and Fast reconstruction of Porous Media from Extremely Limited Information Using Conditional Generative Adversarial Network
Junxi Feng, Xiaohai He, Qizhi Teng +3
Porous media are ubiquitous in both nature and engineering applications, thus their modelling and understanding is of vital importance. In contrast to direct acquisition of three-d…
Capturing the symptoms of malicious code in electronic documents by file's entropy signal combined with Machine learning
Luping Liu, Xiaohai He, Liang Liu +3
Abstract-Email cyber-attacks based on malicious documents have become the popular techniques in today's sophisticated attacks. In the past, persistent efforts have been made to det…
CT-image Super Resolution Using 3D Convolutional Neural Network
Yukai Wang, Qizhi Teng, Xiaohai He +2
Computed Tomography (CT) imaging technique is widely used in geological exploration, medical diagnosis and other fields. In practice, however, the resolution of CT image is usually…
DPW-SDNet: Dual Pixel-Wavelet Domain Deep CNNs for Soft Decoding of JPEG-Compressed Images
Honggang Chen, Xiaohai He, Linbo Qing +2
JPEG is one of the widely used lossy compression methods. JPEG-compressed images usually suffer from compression artifacts including blocking and blurring, especially at low bit-ra…
CISRDCNN: Super-resolution of compressed images using deep convolutional neural networks
Honggang Chen, Xiaohai He, Chao Ren +2
In recent years, much research has been conducted on image super-resolution (SR). To the best of our knowledge, however, few SR methods were concerned with compressed images. The S…
Long-Range Motion Trajectories Extraction of Articulated Human Using Mesh Evolution
Yuanyuan Wu, Xiaohai He, Byeongkeun Kang +2
This letter presents a novel approach to extract reliable dense and long-range motion trajectories of articulated human in a video sequence. Compared with existing approaches that…