Bin Gu
Impact in
-
- Face and Expression Recognition
- Artificial Intelligence top 2%
- Machine Learning and ELM
- Machine Learning and Data Classification
- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
- Imbalanced Data Classification Techniques
- Neural Networks and Applications
Papers in
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- Machine Learning and ELM 31
- Machine Learning and Data Classification 17
- Domain Adaptation and Few-Shot Learning 14
- Stochastic Gradient Optimization Techniques 12
- Machine Learning and Algorithms 12
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- Face and Expression Recognition 34
- Advanced Neural Network Applications 8
- Co-authors
- Victor S. Sheng (8 shared papers)Keng Yeow Tay (1 shared paper)Shuo Li (1 shared paper)Walter M. Romano (1 shared paper)Xingming Sun (1 shared paper)Heng Huang (33 shared papers)Zhouyuan Huo (11 shared papers)Cheng Dan Deng (8 shared papers)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (14 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (6 papers)Neural Networks (5 papers)Pattern Recognition (5 papers)Machine Learning (3 papers)
- Partner nations
- ChinaUnited StatesUnited Arab Emirates
In The Last Decade
Bin Gu
106 papers receiving 1.9k citations
Bin Gu's Hit Papers
Peers
Comparison fields: 5 of 130
- Computer Vision and Pattern Recognition 654
- Artificial Intelligence 933
- Media Technology 106
- Signal Processing 130
- Computer Science Applications 59
Countries citing papers authored by Bin Gu
This map shows the geographic impact of Bin Gu'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 Bin Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bin Gu more than expected).
Fields of papers citing papers by Bin Gu
This network shows the impact of papers produced by Bin Gu. 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 Bin Gu. The network helps show where Bin Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Bin Gu, 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 112 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Incremental Support Vector Learning for Ordinal Regression Hit paper breakdown → | 2014 | 643 |
| 2 | 2016 | 310 | |
| 3 | 2017 | 56 | |
| 4 | 2018 | 47 | |
| 5 | 2006 | 46 | |
| 6 | 2013 | 42 | |
| 7 | 2023 | 33 | |
| 8 | 2020 | 31 | |
| 9 | 2017 | 25 | |
| 10 | 2024 | 24 | |
| 11 | 2017 | 23 | |
| 12 | 2022 | 22 | |
| 13 | 2018 | 22 | |
| 14 | 2011 | 22 | |
| 15 | 2014 | 21 | |
| 16 | 2018 | 21 | |
| 17 | 2020 | 20 | |
| 18 | 2020 | 19 | |
| 19 | 2018 | 19 | |
| 20 | 2018 | 18 |
About Bin Gu
Bin Gu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Signal Processing and Statistics and Probability, having authored 112 papers that have together received 1.9k indexed citations. Recurring topics across this work include Face and Expression Recognition (34 papers), Machine Learning and ELM (31 papers), Machine Learning and Data Classification (17 papers), Sparse and Compressive Sensing Techniques (14 papers), Domain Adaptation and Few-Shot Learning (14 papers), Stochastic Gradient Optimization Techniques (12 papers), Machine Learning and Algorithms (12 papers) and Advanced Neural Network Applications (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (654 citations), Artificial Intelligence (933 citations), Media Technology (106 citations), Signal Processing (130 citations) and Computer Science Applications (59 citations). Bin Gu has collaborated with scholars based in China, United States and United Arab Emirates. Frequent co-authors include Victor S. Sheng, Keng Yeow Tay, Shuo Li, Walter M. Romano, Xingming Sun, Heng Huang, Zhouyuan Huo, Cheng Dan Deng, Zhiyong Gao and Xindong Wu. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, Neural Networks, Pattern Recognition and Machine Learning.
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.