Jun Peng

1.6k citations
163 papers · 1.0k · h-index 16

Impact in

Papers in

Jun Peng

142 papers receiving 979 citations

Peers

Jun Peng
Comparison fields: 5 of 109
  • Computer Vision and Pattern Recognition 252
  • Artificial Intelligence 269
  • Control and Systems Engineering 191
  • Computational Theory and Mathematics 113
  • Statistics, Probability and Uncertainty 46
Replace Shing Chiang Tan with:
Shing Chiang Tan Malaysia
Serge Demidenko Malaysia
Fernando Matı́a Spain
Guanzheng Tan China
Jun Liang China
Stefano Panzieri Italy
Yilin Chen China
Jiyao An China
Ankit Chaudhary India
Jun Peng relative to Shing Chiang Tan Malaysia Shing Chiang Tan's profile →
Citations per field
00.5×3.0×
Shing Chiang Tan · 1×
Citations per year

Countries citing papers authored by Jun Peng

Since Specialization
Citations

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

Fields of papers citing papers by Jun Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 163 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201773
2 201171
3 201168
4 201849
5 200441
6 202337
7 200933
8 201929
9 200223
10 201222
11 200420
12 200818
13 201617
14 201716
15 200516
16 201815
17 200414
18 201514
19 201613
20 201212

About Jun Peng

Jun Peng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems and Computational Theory and Mathematics, having authored 163 papers that have together received 1.0k indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (22 papers), Chaos control and synchronization (12 papers), Neural Networks and Applications (12 papers), Fractal and DNA sequence analysis (11 papers), Cognitive Computing and Networks (10 papers), Service-Oriented Architecture and Web Services (10 papers), Advanced Neural Network Applications (9 papers) and Fuzzy Logic and Control Systems (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (252 citations), Artificial Intelligence (269 citations), Control and Systems Engineering (191 citations), Computational Theory and Mathematics (113 citations) and Statistics, Probability and Uncertainty (46 citations). Jun Peng has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Kincho H. Law, Shangzhu Jin, Shuai Tan, Fuli Wang, Yuqing Chang, Zuojin Li, Xiaofeng Liao, Liukui Chen, Ying Wu and Du Zhang. Their work appears in journals such as The Visual Computer, International Journal of Cognitive Informatics and Natural Intelligence, Scientific Reports, Chemometrics and Intelligent Laboratory Systems and IEEE Transactions on Evolutionary Computation.

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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