Junfeng Yao

97 papers receiving 1.1k citations

Peers

Junfeng Yao
Comparison fields: 5 of 131
  • Computer Vision and Pattern Recognition 306
  • Human-Computer Interaction 60
  • Computational Theory and Mathematics 165
  • Artificial Intelligence 311
  • Industrial and Manufacturing Engineering 90
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Han Liu China
Mohammad Tubishat Jordan
Jiangjiang Zhang China
Liping Xie China
Hamed Shah‐Hosseini Iran
Zuren Feng China
Mohamed Batouche Algeria
Fazhi He China
Qiangfu Zhao Japan
Claudia I. González Mexico
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Citations per field
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Citations per year

Countries citing papers authored by Junfeng Yao

Since Specialization
Citations

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

Fields of papers citing papers by Junfeng Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Junfeng Yao, 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 Junfeng Yao Line = papers co-authored together Junfeng Yao links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010134
2 202377
3 201576
4 200745
5 202045
6 201941
7 202136
8 202235
9 202232
10 202132
11 202130
12 202229
13 201927
14 202126
15 202224
16 201123
17 200621
18 201718
19 201417
20 201817

About Junfeng Yao

Junfeng Yao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Electrical and Electronic Engineering and Aerospace Engineering, having authored 111 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (18 papers), Natural Language Processing Techniques (14 papers), Advanced Image and Video Retrieval Techniques (9 papers), Advanced Vision and Imaging (6 papers), Robotics and Sensor-Based Localization (6 papers), Medical Image Segmentation Techniques (6 papers), Advanced Text Analysis Techniques (6 papers) and Traffic Prediction and Management Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (306 citations), Human-Computer Interaction (60 citations), Computational Theory and Mathematics (165 citations), Artificial Intelligence (311 citations) and Industrial and Manufacturing Engineering (90 citations). Junfeng Yao has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Chunyan Li, Jinsong Su, Chih‐Cheng Hung, Yong Yang, Xiaopeng Zhang, T. E. Simos, Deyi Xiong, Xiangxiang Zeng, Qingqiang Wu and Hong Duan. Their work appears in journals such as The Visual Computer, IEEE Transactions on Neural Networks and Learning Systems, ACM Transactions on Graphics, Information Processing & Management and IEEE/ACM Transactions on Audio Speech and Language Processing.

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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