World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
7427
World Ranking
10584
National Ranking
1302

Overview

Heng-Chao Li is affiliated with Southwest Jiaotong University in China and focuses research on Engineering and Computer Science, with a strong emphasis on Computer Vision and Pattern Recognition, Media Technology, Aerospace Engineering, Atmospheric Science, and Artificial Intelligence.

Their research covers a range of topics related to remote sensing and image processing. These main topics of work include:

  • Remote-Sensing Image Classification
  • Advanced Image Fusion Techniques
  • Remote Sensing and Land Use
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Synthetic Aperture Radar (SAR) Applications and Techniques
  • Advanced SAR Imaging Techniques

Heng-Chao Li has published extensively in prominent venues. Frequent publication venues are:

  • IEEE Transactions on Geoscience and Remote Sensing
  • arXiv (Cornell University)
  • IEEE Geoscience and Remote Sensing Letters
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • SSRN Electronic Journal

Among their recent papers are:

  • Learning Center Probability Map for Detecting Objects in Aerial Images, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • Low-Rank and Sparse Representation for Hyperspectral Image Processing: A review, 2021, IEEE Geoscience and Remote Sensing Magazine
  • Joint Classification of Hyperspectral and LiDAR Data Using Hierarchical Random Walk and Deep CNN Architecture, 2020, IEEE Transactions on Geoscience and Remote Sensing
  • Research Progress on Few-Shot Learning for Remote Sensing Image Interpretation, 2021, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • Spatial-Spectral Feature Extraction via Deep ConvLSTM Neural Networks for Hyperspectral Image Classification, 2020, IEEE Transactions on Geoscience and Remote Sensing

They have collaborated frequently with other researchers in the field. Notable coauthors include:

  • Qian Du
  • Nanqing Liu
  • Turgay Çelik
  • Antonio Plaza
  • Wen-Shuai Hu

Best Publications

  • Deep Convolutional Neural Networks for Hyperspectral Image Classification

    Wei Hu;Yangyu Huang;Li Wei;Fan Zhang

  • Learning Center Probability Map for Detecting Objects in Aerial Images

    Jinwang Wang;Wen Yang;Heng-Chao Li;Haijian Zhang

  • Hyperspectral Anomaly Detection by Fractional Fourier Entropy

    Ran Tao;Xudong Zhao;Wei Li;Heng-Chao Li

  • Low-Rank and Sparse Representation for Hyperspectral Image Processing: A Review

    Jiangtao Peng;Weiwei Sun;Heng-Chao Li;Wei Li

  • On the Empirical-Statistical Modeling of SAR Images With Generalized Gamma Distribution

    Heng-Chao Li;Wen Hong;Yi-Rong Wu;Ping-Zhi Fan

  • Research Progress on Few-Shot Learning for Remote Sensing Image Interpretation

    Xian Sun;Bing Wang;Zhirui Wang;Hao Li

  • Data Augmentation for Hyperspectral Image Classification With Deep CNN

    Wei Li;Chen Chen;Mengmeng Zhang;Hengchao Li

  • Joint Classification of Hyperspectral and LiDAR Data Using Hierarchical Random Walk and Deep CNN Architecture

    Xudong Zhao;Ran Tao;Wei Li;Heng-Chao Li

  • Key techniques for 5G wireless communications: network architecture, physical layer, and MAC layer perspectives

    Unknown

  • Information Fusion for Classification of Hyperspectral and LiDAR Data Using IP-CNN

    Mengmeng Zhang;Wei Li;Ran Tao;Hengchao Li

  • Spatial–Spectral Feature Extraction via Deep ConvLSTM Neural Networks for Hyperspectral Image Classification

    Wen-Shuai Hu;Heng-Chao Li;Lei Pan;Wei Li

  • Spectral–Spatial Weighted Sparse Regression for Hyperspectral Image Unmixing

    Shaoquan Zhang;Jun Li;Heng-Chao Li;Chengzhi Deng

  • Gabor Feature Based Unsupervised Change Detection of Multitemporal SAR Images Based on Two-Level Clustering

    Heng-Chao Li;Turgay Celik;Nathan Longbotham;William J. Emery

  • Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review

    Unknown

  • A³CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification

    Heng-Chao Li;Wen-Shuai Hu;Wei Li;Jun Li

  • Hyperspectral Unmixing Using Sparsity-Constrained Deep Nonnegative Matrix Factorization With Total Variation

    Xin-Ru Feng;Heng-Chao Li;Jun Li;Qian Du

  • An Efficient and Flexible Statistical Model Based on Generalized Gamma Distribution for Amplitude SAR Images

    Heng-Chao Li;Wen Hong;Yi-Rong Wu;Ping-Zhi Fan

  • SNR Enhancement in Phase-Sensitive OTDR with Adaptive 2-D Bilateral Filtering Algorithm

    Haijun He;Liyang Shao;Hengchao Li;Wei Pan

  • Hyperspectral Unmixing Using Double Reweighted Sparse Regression and Total Variation

    Rui Wang;Heng-Chao Li;Aleksandra Pizurica;Jun Li

  • Change Detection in Synthetic Aperture Radar Images Using a Dual-Domain Network

    Xiaofan Qu;Feng Gao;Junyu Dong;Qian Du

  • Multi-Aspect-Aware Bidirectional LSTM Networks for Synthetic Aperture Radar Target Recognition

    Fan Zhang;Chen Hu;Qiang Yin;Wei Li

  • Data-Driven Distributed Optical Vibration Sensors: A Review

    Li-Yang Shao;Shuaiqi Liu;Sankhyabrata Bandyopadhyay;Feihong Yu

  • Robust Capsule Network Based on Maximum Correntropy Criterion for Hyperspectral Image Classification

    Heng-Chao Li;Wei-Ye Wang;Lei Pan;Wei Li

  • Discriminant Analysis-Based Dimension Reduction for Hyperspectral Image Classification: A Survey of the Most Recent Advances and an Experimental Comparison of Different Techniques

    Wei Li;Fubiao Feng;Hengchao Li;Qian Du

Frequent Co-Authors

Qian Du
Qian Du Mississippi State University
William J. Emery
William J. Emery University of Colorado Boulder
Turgay Celik
Turgay Celik University of the Witwatersrand
Wei Li
Wei Li Beijing Institute of Technology
Wenzhi Liao
Wenzhi Liao Ghent University
Antonio Plaza
Antonio Plaza University of Extremadura
Kun Fu
Kun Fu University of Chinese Academy of Sciences
Wilfried Philips
Wilfried Philips Ghent University
Ran Tao
Ran Tao Beijing Institute of Technology
Pingzhi Fan
Pingzhi Fan Southwest Jiaotong University

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

Studying Computer Science in the USA opens up a range of flexible online degree options for students at all stages. If you’re seeking to quickly advance your qualifications, consider exploring the fastest masters degree online programs. These accelerated options are designed for professionals aiming to boost their careers without taking a lengthy break from work.

For those focused on long-term job prospects, researching the most worthwhile masters degrees can help you select a program that aligns with market demand and your career goals. Not everyone needs to jump into a master's program immediately; an associate degree online provides a flexible and affordable pathway to build foundational computer science skills.

Cost is often a barrier, but there are cheap online college classes available, making quality education more accessible. Whether you’re just starting out with an associate degree or considering a fast-tracked master's, online programs offer diverse pathways to a successful computer science career in the USA.

Best Scientists Citing Heng-Chao Li

Trending Scientists