Xinjun Peng

1.8k citations
46 papers · 1.5k · 1 hit paper · h-index 20

Impact in

Papers in

Xinjun Peng

46 papers receiving 1.4k citations

Hit Papers

TSVR: An efficient Twin Support Vector Machine for regression 2009 · 372 citations
3720+5+11Years since publication100200300

Peers

Xinjun Peng
Comparison fields: 5 of 101
  • Computer Vision and Pattern Recognition 960
  • Artificial Intelligence 856
  • Control and Systems Engineering 434
  • Media Technology 119
  • Analytical Chemistry 129
Replace Yitian Xu with:
Yitian Xu China
Takashi Onoda Japan
M. Markou United Kingdom
Weida Zhou China
Lingfeng Niu China
Xijiong Xie China
Claudia I. González Mexico
Pei-Yi Hao Taiwan
Yi-Ren Yeh Taiwan
Xinjun Peng relative to Yitian Xu China Yitian Xu's profile →
Citations per field
00.5×1.7×
Yitian Xu · 1×
Citations per year

Countries citing papers authored by Xinjun Peng

Since Specialization
Citations

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

Fields of papers citing papers by Xinjun Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Xinjun 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 Xinjun Peng Line = papers co-authored together Xinjun Peng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1
TSVR: An efficient Twin Support Vector Machine for regression
Hit paper breakdown →
2009372
2 2011174
3 2010121
4 201265
5 201055
6 201152
7 201146
8 200940
9 201239
10 201634
11 201834
12 201432
13 201430
14 201328
15 201025
16 201324
17 201321
18 201121
19 200720
20 201219

About Xinjun Peng

Xinjun Peng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Molecular Biology and Media Technology, having authored 46 papers that have together received 1.5k indexed citations. Recurring topics across this work include Face and Expression Recognition (36 papers), Advanced Algorithms and Applications (20 papers), Machine Learning and ELM (8 papers), Neural Networks and Applications (7 papers), Remote-Sensing Image Classification (7 papers), Image Retrieval and Classification Techniques (6 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Metaheuristic Optimization Algorithms Research (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (960 citations), Artificial Intelligence (856 citations), Control and Systems Engineering (434 citations), Media Technology (119 citations) and Analytical Chemistry (129 citations). Xinjun Peng has collaborated with scholars based in China. Frequent co-authors include Dong Xu, De Chen, Jindong Shen, Yifei Wang, Wen Zhou, Yifei Wang, Yifei Wang, Yifei Wang and Xiang Liu. Their work appears in journals such as Neurocomputing, Information Sciences, Neural Computing and Applications, Expert Systems with Applications and Applied Mathematics and Mechanics.

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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