Bin Gu
Impact in
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- Face and Expression Recognition
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 5%
- Machine Learning and ELM
- Privacy-Preserving Technologies in Data
- Imbalanced Data Classification Techniques
- Text and Document Classification Technologies
- Machine Learning and Data Classification
Papers in
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- Neural Networks and Applications 2
- Stochastic Gradient Optimization Techniques 2
- Machine Learning and ELM 2
- Domain Adaptation and Few-Shot Learning 1
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- Face and Expression Recognition 4
- Co-authors
- Victor S. Sheng (5 shared papers)Shuo Li (5 shared papers)Zhijie Wang (2 shared papers)Derek Ho (1 shared paper)Said Osman (1 shared paper)Heng Huang (2 shared papers)Keng Yeow Tay (1 shared paper)Walter Romano (1 shared paper)
- Journals
- IEEE Transactions on Biomedical Engineering (1 paper)Information Sciences (1 paper)Climate Dynamics (1 paper)Neural Networks (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Bin Gu
10 papers receiving 986 citations
Bin Gu's Hit Papers
Peers
Comparison fields: 5 of 111
- Computer Vision and Pattern Recognition 330
- Artificial Intelligence 414
- Media Technology 70
- Signal Processing 61
- Computer Networks and Communications 117
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 18 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
| # | Work | ||
|---|---|---|---|
| 1 | A Robust Regularization Path Algorithm for $\nu $ -Support Vector Classification Hit paper breakdown → | 2016 | 399 |
| 2 | Incremental learning for Hit paper breakdown → | 2015 | 383 |
| 3 | 2016 | 57 | |
| 4 | Bi-parameter space partition for cost-sensitive SVM | 2015 | 48 |
| 5 | 2014 | 45 | |
| 6 | 2020 | 41 | |
| 7 | 2018 | 15 | |
| 8 | 2017 | 7 | |
| 9 | 2022 | 3 | |
| 10 | 2021 | 2 |
About Bin Gu
Bin Gu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Economics and Econometrics and Computer Networks and Communications, having authored 10 papers that have together received 1000 indexed citations. Recurring topics across this work include Face and Expression Recognition (4 papers), Complex Systems and Time Series Analysis (2 papers), Neural Networks and Applications (2 papers), Stochastic Gradient Optimization Techniques (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Machine Learning and ELM (2 papers), Ecosystem dynamics and resilience (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (330 citations), Artificial Intelligence (414 citations), Media Technology (70 citations), Signal Processing (61 citations) and Computer Networks and Communications (117 citations). Bin Gu has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Victor S. Sheng, Shuo Li, Zhijie Wang, Derek Ho, Said Osman, Heng Huang, Keng Yeow Tay, Walter Romano, Xiang Li and Aashish Goela. Their work appears in journals such as IEEE Transactions on Biomedical Engineering, Information Sciences, Climate Dynamics, Neural Networks and IEEE Transactions on Neural Networks and Learning Systems.
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.