World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
4429
World Ranking
12249
National Ranking
1509

Overview

Xiaohai He is affiliated with Sichuan University in China and has an extensive research portfolio primarily focused on computer science and engineering. Their work spans several core areas including computer vision and pattern recognition, media technology, artificial intelligence, signal processing, and ocean engineering.

Their research topics cover a broad range of subjects within advanced image and signal processing. Key themes include:

  • Advanced Image Processing Techniques
  • Image and Signal Denoising Methods
  • Advanced Vision and Imaging
  • Advanced Image Fusion Techniques
  • Image Processing Techniques and Applications
  • Video Coding and Compression Technologies
  • Medical Image Segmentation Techniques

Xiaohai He's publication record includes articles in frequently appearing venues such as:

  • Physical Review. E
  • IEEE Signal Processing Letters
  • Journal of Electronic Imaging
  • IEEE Transactions on Circuits and Systems for Video Technology
  • IEEE Transactions on Broadcasting

Recent notable papers include:

  • Real-world single image super-resolution: A brief review (2021, Information Fusion)
  • An end-to-end three-dimensional reconstruction framework of porous media from a single two-dimensional image based on deep learning (2020, Computer Methods in Applied Mechanics and Engineering)
  • BPGAN: Brain PET synthesis from MRI using generative adversarial network for multi-modal Alzheimer's disease diagnosis (2022, Computer Methods and Programs in Biomedicine)
  • Super-resolution of real-world rock microcomputed tomography images using cycle-consistent generative adversarial networks (2020, Physical Review. E)
  • Slice-to-voxel stochastic reconstructions on porous media with hybrid deep generative model (2020, Computational Materials Science)

Their research collaborations include repeated partnerships with several frequent co-authors, such as:

  • Linbo Qing (co-authored 35 papers)
  • Qizhi Teng (34 papers)
  • Honggang Chen (27 papers)
  • Chao Ren (27 papers)
  • Shuhua Xiong (19 papers)

Xiaohai He's body of work contributes to the fields of advanced image processing, machine learning applications in vision tasks, and signal enhancement techniques. Their studies encompass both theoretical frameworks and practical implementations, addressing challenges such as super-resolution imaging, image fusion, and multi-modal data interpretation.

Best Publications

  • Real-World Single Image Super-Resolution: A Brief Review

    Honggang Chen;Xiaohai He;Linbo Qing;Yuanyuan Wu

  • Adaptive Consistency Prior based Deep Network for Image Denoising

    Chao Ren;Xiaohai He;Chuncheng Wang;Zhibo Zhao

  • Infrared and visible image fusion with the use of multi-scale edge-preserving decomposition and guided image filter

    Wei Gan;Xiaohong Wu;Wei Wu;Xiaomin Yang

  • CT-image of rock samples super resolution using 3D convolutional neural network

    Yukai Wang;Qizhi Teng;Xiaohai He;Junxi Feng

  • An end-to-end three-dimensional reconstruction framework of porous media from a single two-dimensional image based on deep learning

    Junxi Feng;Qizhi Teng;Qizhi Teng;Bing Li;Xiaohai He;Xiaohai He

  • BPGAN: Brain PET synthesis from MRI using generative adversarial network for multi-modal Alzheimer's disease diagnosis

    Unknown

  • Accelerating multi-point statistics reconstruction method for porous media via deep learning

    Junxi Feng;Qizhi Teng;Xiaohai He;Xiaohong Wu

  • Reconstruction of porous media from extremely limited information using conditional generative adversarial networks.

    Junxi Feng;Xiaohai He;Qizhi Teng;Chao Ren

  • Learning-based super resolution using kernel partial least squares

    Wei Wu;Zheng Liu;Xiaohai He

  • Moving Object Detection With a Freely Moving Camera via Background Motion Subtraction

    Yuanyuan Wu;Xiaohai He;Truong Q. Nguyen

  • Super-resolution of real-world rock microcomputed tomography images using cycle-consistent generative adversarial networks

    Honggang Chen;Xiaohai He;Xiaohai He;Qizhi Teng;Raymond E. Sheriff

  • An automated vision system for container-code recognition

    Wei Wu;Zheng Liu;Mo Chen;Xiaomin Yang

  • DPW-SDNet: Dual Pixel-Wavelet Domain Deep CNNs for Soft Decoding of JPEG-Compressed Images

    Unknown

  • Object tracking using firefly algorithm

    Ming-Liang Gao;Xiao-Hai He;Dai-Sheng Luo;Jun Jiang

  • A pixel selection rule based on the number of different-phase neighbours for the simulated annealing reconstruction of sandstone microstructure.

    T. Tang;Q. Teng;X. He;D. Luo

  • Slice-to-voxel stochastic reconstructions on porous media with hybrid deep generative model

    Fan Zhang;Fan Zhang;Qizhi Teng;Qizhi Teng;Honggang Chen;Honggang Chen;Xiaohai He;Xiaohai He

  • Single Image Super-Resolution Using Local Geometric Duality and Non-Local Similarity

    Chao Ren;Xiaohai He;Qizhi Teng;Yuanyuan Wu

  • Single Image Super-Resolution via Adaptive High-Dimensional Non-Local Total Variation and Adaptive Geometric Feature

    Chao Ren;Xiaohai He;Truong Q. Nguyen

  • Video superresolution reconstruction based on subpixel registration and iterative back projection

    Feng-qing Qin;Xiao-hai He;Wei-long Chen;Xiao-min Yang

  • Diagnosis of Alzheimer's disease based on regional attention with sMRI gray matter slices.

    Yanteng Zhang;Qizhi Teng;Yuyang Liu;Yan Liu

  • Single-image super-resolution based on Markov random field and contourlet transform

    Wei Wu;Zheng Liu;Wail Gueaieb;Xiaohai He

  • Reconstruction of three-dimensional porous media from a single two-dimensional image using three-step sampling.

    MingLiang Gao;XiaoHai He;QiZhi Teng;Chen Zuo

  • Stable-phase method for hierarchical annealing in the reconstruction of porous media images.

    DongDong Chen;Qizhi Teng;Xiaohai He;Zhi Xu

Frequent Co-Authors

Truong Q. Nguyen
Truong Q. Nguyen University of California, San Diego
Zheng Liu
Zheng Liu University of British Columbia
Ce Zhu
Ce Zhu University of Electronic Science and Technology of China
Andreia V. Faria
Andreia V. Faria Johns Hopkins University School of Medicine

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