Guang-Bin Huang
Impact in
- Artificial Intelligence top 0.01%
- Machine Learning and ELM
- Neural Networks and Applications
- Domain Adaptation and Few-Shot Learning
- Computer Vision and Pattern Recognition top 0.05%
- Face and Expression Recognition
Papers in
-
- Machine Learning and ELM 120
- Neural Networks and Applications 68
- Domain Adaptation and Few-Shot Learning 40
- Stochastic Gradient Optimization Techniques 10
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- Face and Expression Recognition 44
- Co-authors
- Qinyu Zhu (5 shared papers)Chee‐Kheong Siew (10 shared papers)Hongming Zhou (7 shared papers)Xiaojian Ding (2 shared papers)Rui Zhang (1 shared paper)P. Saratchandran (20 shared papers)Qin‐Yu Zhu (2 shared papers)Lihui Chen (2 shared papers)
- Journals
- Neurocomputing (36 papers)Neural Networks (9 papers)IEEE Transactions on Cybernetics (8 papers)IEEE Transactions on Neural Networks and Learning Systems (5 papers)IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) (5 papers)
- Partner nations
- SingaporeChinaUnited States
In The Last Decade
Guang-Bin Huang
208 papers receiving 40.3k citations
Guang-Bin Huang's Hit Papers
Peers
Comparison fields: 5 of 212
- Artificial Intelligence 29.4k
- Computer Vision and Pattern Recognition 7.8k
- Control and Systems Engineering 4.9k
- Electrical and Electronic Engineering 10.6k
- Media Technology 1.5k
Countries citing papers authored by Guang-Bin Huang
This map shows the geographic impact of Guang-Bin Huang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Guang-Bin Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guang-Bin Huang more than expected).
Fields of papers citing papers by Guang-Bin Huang
This network shows the impact of papers produced by Guang-Bin Huang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Guang-Bin Huang. The network helps show where Guang-Bin Huang may publish in the future.
Co-authors
The 25 scholars most cited alongside Guang-Bin Huang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 212 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Extreme learning machine: Theory and applications Hit paper breakdown → | 2006 | 9872 |
| 2 | Extreme Learning Machine for Regression and Multiclass Classification Hit paper breakdown → | 2011 | 4352 |
| 3 | Extreme learning machine: a new learning scheme of feedforward neural networks Hit paper breakdown → | 2005 | 3093 |
| 4 | Universal Approximation using Incremental Constructive Feedforward Networks with Random Hidden Nodes Hit paper breakdown → | 2006 | 1979 |
| 5 | A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks Hit paper breakdown → | 2006 | 1522 |
| 6 | Extreme learning machines: a survey Hit paper breakdown → | 2011 | 1462 |
| 7 | Trends in extreme learning machines: A review Hit paper breakdown → | 2014 | 1344 |
| 8 | Extreme Learning Machine for Multilayer Perceptron Hit paper breakdown → | 2015 | 1135 |
| 9 | Convex incremental extreme learning machine Hit paper breakdown → | 2007 | 877 |
| 10 | An Insight into Extreme Learning Machines: Random Neurons, Random Features and Kernels Hit paper breakdown → | 2014 | 756 |
| 11 | Enhanced random search based incremental extreme learning machine Hit paper breakdown → | 2007 | 693 |
| 12 | Optimization method based extreme learning machine for classification Hit paper breakdown → | 2010 | 676 |
| 13 | Evolutionary extreme learning machine Hit paper breakdown → | 2005 | 629 |
| 14 | Learning capability and storage capacity of two-hidden-layer feedforward networks Hit paper breakdown → | 2003 | 613 |
| 15 | Weighted extreme learning machine for imbalance learning Hit paper breakdown → | 2012 | 568 |
| 16 | A Generalized Growing and Pruning RBF (GGAP-RBF) Neural Network for Function Approximation Hit paper breakdown → | 2005 | 508 |
| 17 | Error Minimized Extreme Learning Machine With Growth of Hidden Nodes and Incremental Learning Hit paper breakdown → | 2009 | 496 |
| 18 | What are Extreme Learning Machines? Filling the Gap Between Frank Rosenblatt’s Dream and John von Neumann’s Puzzle Hit paper breakdown → | 2015 | 363 |
| 19 | Novel Weighting-Delay-Based Stability Criteria for Recurrent Neural Networks With Time-Varying Delay Hit paper breakdown → | 2009 | 348 |
| 20 | Robust Global Exponential Synchronization of Uncertain Chaotic Delayed Neural Networks via Dual-Stage Impulsive Control Hit paper breakdown → | 2009 | 337 |
About Guang-Bin Huang
Guang-Bin Huang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Control and Systems Engineering and Biomedical Engineering, having authored 212 papers that have together received 41.6k indexed citations. Recurring topics across this work include Machine Learning and ELM (120 papers), Neural Networks and Applications (68 papers), Face and Expression Recognition (44 papers), Advanced Memory and Neural Computing (44 papers), Domain Adaptation and Few-Shot Learning (40 papers), Stochastic Gradient Optimization Techniques (10 papers), MicroRNA in disease regulation (9 papers) and Advanced Algorithms and Applications (7 papers). The work is most often cited by research in Artificial Intelligence (29.4k citations), Computer Vision and Pattern Recognition (7.8k citations), Control and Systems Engineering (4.9k citations), Electrical and Electronic Engineering (10.6k citations) and Media Technology (1.5k citations). Guang-Bin Huang has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include Qinyu Zhu, Chee‐Kheong Siew, Hongming Zhou, Xiaojian Ding, Rui Zhang, P. Saratchandran, Qin‐Yu Zhu, Lihui Chen, Yuan Lan and Lei Chen. Their work appears in journals such as Neurocomputing, Neural Networks, IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.