Jing Peng
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 10%
- Media Technology top 5%
- Aerospace Engineering
- Co-authors
- Carlotta DomeniconiDimitrios GunopulosAnna FeldmanBikramjit BanerjeeWei FanBir BhanuKun ZhangJiangtao Ren
- Topics
- Face and Expression Recognition (21 papers)Natural Language Processing Techniques (12 papers)Topic Modeling (8 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsAnalytica Chimica Acta
- Partner nations
- United StatesChinaCanada
In The Last Decade
Jing Peng
75 papers receiving 800 citations
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 453
- Computer Vision and Pattern Recognition 282
- Information Systems 59
- Media Technology 57
- Aerospace Engineering 56
Countries citing papers authored by Jing Peng
This map shows the geographic impact of Jing Peng'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 Jing Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Peng more than expected).
Fields of papers citing papers by Jing Peng
This network shows the impact of papers produced by Jing Peng. 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 Jing Peng. The network helps show where Jing Peng may publish in the future.
Co-authorship network of co-authors of Jing Peng
This figure shows the co-authorship network connecting the top 25 collaborators of Jing Peng. A scholar is included among the top collaborators of Jing Peng 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 Jing Peng. Jing Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 2 | |
| 3 | 5 | |
| 4 | 14 | |
| 5 | 1 | |
| 6 | 7 | |
| 7 | Designing a Russian Idiom-Annotated Corpus | 3 |
| 8 | 2 | |
| 9 | 8 | |
| 10 | 18 | |
| 11 | Classifying Idiomatic and Literal Expressions Using Vector Space Representations | 5 |
| 12 | Application of acoustic emission technique to full scale aircraft fatigue tests | 1 |
| 13 | Measure of Individual Tacit Knowledge and its Application in R & D Team | 0 |
| 14 | Automatic Classification of Article Errors in L2 Written English | 3 |
| 15 | 7 | |
| 16 | 19 | |
| 17 | 6 | |
| 18 | Performance bounded reinforcement learning in strategic interactions | 25 |
| 19 | 4 | |
| 20 | 3 |
About Jing Peng
Jing Peng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 86 papers that have together received 844 indexed citations. Recurring topics across this work include Face and Expression Recognition (21 papers), Natural Language Processing Techniques (12 papers) and Topic Modeling (8 papers). The work is most often cited by research in Artificial Intelligence (453 citations), Computer Vision and Pattern Recognition (282 citations) and Media Technology (57 citations). Jing Peng has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Carlotta Domeniconi, Dimitrios Gunopulos, Anna Feldman, Bikramjit Banerjee, Wei Fan, Bir Bhanu, Kun Zhang, Jiangtao Ren, Olivier Verscheure and Erheng Zhong. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Analytica Chimica Acta.
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.