Xinjun Peng

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

Impact in

Papers in

Xinjun Peng

46 papers receiving 1.5k citations

Xinjun Peng's Hit Papers

TSVR: An efficient Twin Support Vector Machine for regression 2009 · 393 citations
3930+5+11Years since publication100200300

Peers

Xinjun Peng
Comparison fields: 5 of 100
  • Computer Vision and Pattern Recognition 1.0k
  • Artificial Intelligence 905
  • Control and Systems Engineering 463
  • Analytical Chemistry 134
  • Media Technology 124
Replace Yitian Xu with:
Yitian Xu China
Takashi Onoda Japan
Lei Wu China
José R. Dorronsoro Spain
M. Markou United Kingdom
Weida Zhou China
Pei-Yi Hao Taiwan
Lingfeng Niu China
Kai-Bo Duan Singapore
Yi-Ren Yeh Taiwan
Xinjun Peng relative to Yitian Xu China Yitian Xu's profile →
Citations per field
00.5×1.5×1.8×
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 10 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 47 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 →
2009393
2 2011190
3 2010127
4 201267
5 201063
6 201153
7 201151
8 201242
9 200941
10 201636
11 201433
12 201833
13 201432
14 201330
15 201026
16 201325
17 201122
18 200721
19 201321
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 47 papers that have together received 1.5k indexed citations. Recurring topics across this work include Face and Expression Recognition (37 papers), Advanced Algorithms and Applications (21 papers), Machine Learning and ELM (8 papers), Remote-Sensing Image Classification (7 papers), Neural Networks and Applications (7 papers), Image Retrieval and Classification Techniques (6 papers), Metaheuristic Optimization Algorithms Research (5 papers) and Advanced Image and Video Retrieval Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.0k citations), Artificial Intelligence (905 citations), Control and Systems Engineering (463 citations), Analytical Chemistry (134 citations) and Media Technology (124 citations). Xinjun Peng has collaborated with scholars based in China. Frequent co-authors include Dong Xu, De Chen, Yifei Wang, 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, Expert Systems with Applications, Neural Computing and Applications and Knowledge-Based Systems.

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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