World's Best Scientists 2026 revealed!
Jonathan Cheung-Wai Chan

Jonathan Cheung-Wai Chan

D-Index & Metrics

Computer Science

D-Index
43
Citations
7747
World Ranking
7989
National Ranking
79

Overview

Jonathan Cheung-Wai Chan is affiliated with Vrije Universiteit Brussel in Belgium. Their research primarily spans the fields of Engineering and Computer Science, with a focus on Media Technology, Computer Vision and Pattern Recognition, Computational Mechanics, Atmospheric Science, and Artificial Intelligence.

The scientist's work centers on various core topics, including:

  • Remote-Sensing Image Classification
  • Advanced Image Fusion Techniques
  • Image and Signal Denoising Methods
  • Sparse and Compressive Sensing Techniques
  • Remote Sensing and Land Use
  • Tensor decomposition and applications
  • Image Enhancement Techniques

Jonathan Cheung-Wai Chan has an extensive publication record in several key academic venues. The most frequent publication outlets include:

  • Remote Sensing
  • IEEE Transactions on Geoscience and Remote Sensing
  • ISPRS Journal of Photogrammetry and Remote Sensing
  • IEEE Geoscience and Remote Sensing Letters
  • IEEE Transactions on Neural Networks and Learning Systems

Some of the recent papers authored or co-authored by the scientist are:

  • "Spatial-Spectral Structured Sparse Low-Rank Representation for Hyperspectral Image Super-Resolution," 2021, IEEE Transactions on Image Processing
  • "Multilayer Sparsity-Based Tensor Decomposition for Low-Rank Tensor Completion," 2021, IEEE Transactions on Neural Networks and Learning Systems
  • "Automatic depression recognition using CNN with attention mechanism from videos," 2020, Neurocomputing
  • "When Laplacian Scale Mixture Meets Three-Layer Transform: A Parametric Tensor Sparsity for Tensor Completion," 2022, IEEE Transactions on Cybernetics
  • "Collaborative learning of lightweight convolutional neural network and deep clustering for hyperspectral image semi-supervised classification with limited training samples," 2020, ISPRS Journal of Photogrammetry and Remote Sensing

The scientist frequently collaborates with a number of researchers, including:

  • Yongqiang Zhao
  • Seong G. Kong
  • Jize Xue
  • Yuanyang Bu
  • Jingxiang Yang

Best Publications

  • Evaluation of random forest and adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery

    Jonathan Cheung-Wai Chan;Desiré Paelinckx

  • Random forest regression for online capacity estimation of lithium-ion batteries

    Yi Li;Changfu Zou;Maitane Berecibar;Elise Nanini-Maury

  • Learning and Transferring Deep Joint Spectral–Spatial Features for Hyperspectral Classification

    Jingxiang Yang;Yong-Qiang Zhao;Jonathan Cheung-Wai Chan

  • Multiple Criteria for Evaluating Machine Learning Algorithms for Land Cover Classification from Satellite Data

    Ruth Defries;Jonathan Cheung-Wai Chan

  • Detecting the nature of change in an urban environment : A comparison of machine learning algorithms

    Jonathan Cheung-Wai Chan;Kwok-Ping Chan;Anthony Gar-On Yeh

  • Nonlocal Low-Rank Regularized Tensor Decomposition for Hyperspectral Image Denoising

    Jize Xue;Yongqiang Zhao;Wenzhi Liao;Jonathan Cheung-Wai Chan

  • Hyperspectral and Multispectral Image Fusion via Deep Two-Branches Convolutional Neural Network

    Jingxiang Yang;Yong-Qiang Zhao;Jonathan Cheung-Wai Chan

  • Multilayer Sparsity-Based Tensor Decomposition for Low-Rank Tensor Completion.

    Jize Xue;Yongqiang Zhao;Shaoguang Huang;Wenzhi Liao

  • Spatial-Spectral Structured Sparse Low-Rank Representation for Hyperspectral Image Super-Resolution

    Jize Xue;Yong-Qiang Zhao;Yuanyang Bu;Wenzhi Liao

  • Potential of Resolution-Enhanced Hyperspectral Data for Mineral Mapping Using Simulated EnMAP and Sentinel-2 Images

    Naoto Yokoya;Jonathan Cheung-Wai Chan;Karl Segl

  • Hyperspectral Images Classification Based on Dense Convolutional Networks with Spectral-Wise Attention Mechanism

    Bei Fang;Ying Li;Haokui Zhang;Jonathan Cheung Wai Chan

  • When Laplacian Scale Mixture Meets Three-Layer Transform: A Parametric Tensor Sparsity for Tensor Completion

    Unknown

  • Automatic depression recognition using CNN with attention mechanism from videos

    Lang He;Jonathan Cheung-Wai Chan;Zhongmin Wang

  • Hyperspectral image classification using two-channel deep convolutional neural network

    Jingxiang Yang;Yongqiang Zhao;Jonathan Cheung-Wai Chan;Chen Yi

  • Improved Classification of VHR Images of Urban Areas Using Directional Morphological Profiles

    Rik Bellens;Sidharta Gautama;Leyden Martinez-Fonte;Wilfried Philips

  • Fully Automatic Subpixel Image Registration of Multiangle CHRIS/Proba Data

    Jianglin Ma;Jonathan Cheung-Wai Chan;Frank Canters

  • An Iterative Image Dehazing Method With Polarization

    Linghao Shen;Yongqiang Zhao;Qunnie Peng;Jonathan Cheung-Wai Chan

  • Enhanced algorithm performance for land cover classification from remotely sensed data using bagging and boosting

    Jonathan Cheung-Wai Chan;Chengquan Huang;R. DeFries

  • Coupled Sparse Denoising and Unmixing With Low-Rank Constraint for Hyperspectral Image

    Jingxiang Yang;Yong-qiang Zhao;Jonathan Cheung-Wai Chan;Seong G. Kong

  • Thin cloud removal with residual symmetrical concatenation network

    Wenbo Li;Wenbo Li;Ying Li;Di Chen;Jonathan Cheung-Wai Chan

  • Qualitative distinction of congeneric and introgressive mangrove species in mixed patchy forest assemblages using high spatial resolution remotely sensed imagery (IKONOS)

    Farid Dahdouh-Guebas;Elly Van Hiel;Jonathan Cheung-Wai Chan;Loku Pupukkittige Jayatissa

  • Hyperspectral Imagery Super-Resolution by Spatial-Spectral Joint Nonlocal Similarity

    Yongqiang Zhao;Jingxiang Yang;Jonathan Cheung-Wai Chan

Frequent Co-Authors

Wenzhi Liao
Wenzhi Liao Ghent University
Ruth S. DeFries
Ruth S. DeFries Columbia University
Okke Batelaan
Okke Batelaan Flinders University
Quan Pan
Quan Pan Northwestern Polytechnical University
Naoto Yokoya
Naoto Yokoya University of Tokyo
Wilfried Philips
Wilfried Philips Ghent University
John R. Townshend
John R. Townshend University of Maryland, College Park
Chengquan Huang
Chengquan Huang University of Maryland, College Park
Franco Miglietta
Franco Miglietta National Research Council (CNR)
Maitane Berecibar
Maitane Berecibar Vrije Universiteit Brussel

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Pursuing Computer Science in the USA opens doors to a variety of flexible academic and career options. Today’s students often consider online learning for convenience and speed. If you want to enter the tech industry quickly, look into certifications for jobs that are in demand. These can help you gain practical skills and boost your resume in just a few weeks or months.

For those aiming to fast-track their education, exploring the fastest masters degree online options can be a smart move. These accelerated programs help you gain advanced credentials and move up the career ladder faster—without leaving your current job.

When selecting a graduate program, consider which degrees truly provide the best value for your investment. Check out the masters degrees that are worth it to find programs with high employer demand and better earning potential.

If you’re just starting out or switching careers, online associate degree programs in computer science can provide a solid foundation and lead to entry-level positions or further study. Whichever pathway you choose, online education offers flexibility and accessibility for students worldwide.

Best Scientists Citing Jonathan Cheung-Wai Chan

Trending Scientists

Recently Published Articles