Bingyi Kang
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 2%
- Media Technology top 5%
- Radiology, Nuclear Medicine and Imaging
- Industrial and Manufacturing Engineering top 10%
- Co-authors
- Jiashi FengZhuang LiuFisher YuXin WangTrevor DarrellShuicheng YanBryan HooiYifan Zhang
- Topics
- Domain Adaptation and Few-Shot Learning (5 papers)Multimodal Machine Learning Applications (3 papers)Advanced Neural Network Applications (2 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceLecture notes in computer scienceUncertainty in Artificial Intelligence
- Partner nations
- SingaporeChinaUnited States
In The Last Decade
Bingyi Kang
6 papers receiving 796 citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Computer Vision and Pattern Recognition 494
- Artificial Intelligence 487
- Media Technology 90
- Radiology, Nuclear Medicine and Imaging 82
- Industrial and Manufacturing Engineering 57
Countries citing papers authored by Bingyi Kang
This map shows the geographic impact of Bingyi Kang'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 Bingyi Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bingyi Kang more than expected).
Fields of papers citing papers by Bingyi Kang
This network shows the impact of papers produced by Bingyi Kang. 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 Bingyi Kang. The network helps show where Bingyi Kang may publish in the future.
Co-authorship network of co-authors of Bingyi Kang
This figure shows the co-authorship network connecting the top 25 collaborators of Bingyi Kang. A scholar is included among the top collaborators of Bingyi Kang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bingyi Kang. Bingyi Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Deep Long-Tailed Learning: A Surveybreakdown → | 268 |
| 3 | Exploring Balanced Feature Spaces for Representation Learning | 53 |
| 4 | 11 | |
| 5 | Few-Shot Object Detection via Feature Reweightingbreakdown → | 468 |
| 6 | Transferable Meta Learning Across Domains | 14 |
About Bingyi Kang
Bingyi Kang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Industrial and Manufacturing Engineering, having authored 6 papers that have together received 815 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (3 papers) and Advanced Neural Network Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (494 citations), Artificial Intelligence (487 citations) and Media Technology (90 citations). Bingyi Kang has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include Jiashi Feng, Zhuang Liu, Fisher Yu, Xin Wang, Trevor Darrell, Shuicheng Yan, Bryan Hooi, Yifan Zhang, Zehuan Yuan and Yu Li. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Lecture notes in computer science and Uncertainty in Artificial Intelligence.
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.