Yi Bin

1.9k citations
85 papers · 1.1k · h-index 15

Impact in

    • Multimodal Machine Learning Applications
    • Advanced Image and Video Retrieval Techniques
    • Human Pose and Action Recognition
    • Video Analysis and Summarization
    • Image Retrieval and Classification Techniques
    • Domain Adaptation and Few-Shot Learning
    • Topic Modeling
    • Natural Language Processing Techniques

Papers in

Yi Bin

76 papers receiving 1.1k citations

Peers

Yi Bin
Comparison fields: 5 of 120
  • Computer Vision and Pattern Recognition 632
  • Artificial Intelligence 421
  • Health Informatics 8
  • Media Technology 40
  • Software 18
Replace Kun Wei with:
Kun Wei China
Frédéric Bastien Canada
D.W. Ruck United States
Matthias Humt Germany
Huamin Yang China
Pavel Lyakhov Russia
Zhongchao Shi China
Keke Tang China
Yi Bin relative to Kun Wei China Kun Wei's profile →
Citations per field
00.5×4.7×
Kun Wei · 1×
Citations per year

Countries citing papers authored by Yi Bin

Since Specialization
Citations

This map shows the geographic impact of Yi Bin'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 Yi Bin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Bin more than expected).

Fields of papers citing papers by Yi Bin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi Bin. 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 Yi Bin. The network helps show where Yi Bin may publish in the future.

Co-authors

The 25 scholars most cited alongside Yi Bin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yi Bin Line = papers co-authored together Yi Bin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018217
2 2018169
3 202089
4 201653
5 202134
6 202334
7 201733
8 202132
9 202230
10 201826
11 202323
12 201723
13 201918
14 201518
15 201715
16 202114
17 202114
18 202413
19 202413
20 202112

About Yi Bin

Yi Bin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering, Oceanography and Astronomy and Astrophysics, having authored 85 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (17 papers), Multimodal Machine Learning Applications (15 papers), GNSS positioning and interference (10 papers), Geophysics and Gravity Measurements (9 papers), Generative Adversarial Networks and Image Synthesis (6 papers), Ionosphere and magnetosphere dynamics (6 papers), Human Pose and Action Recognition (5 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (632 citations), Artificial Intelligence (421 citations), Health Informatics (8 citations), Media Technology (40 citations) and Software (18 citations). Yi Bin has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Yang Yang, Heng Tao Shen, Fumin Shen, Ning Xie, Jie Zhou, Yanli Ji, Alan Hanjalić, Guoqing Wang, Xing Xu and Yujuan Ding. Their work appears in journals such as IEEE Transactions on Multimedia, Advances in Space Research, IEEE Transactions on Circuits and Systems for Video Technology, Remote Sensing and Chinese Journal of Aeronautics.

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.

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