Jun He

2.4k citations
174 papers · 1.6k · h-index 23

Impact in

Papers in

Jun He

154 papers receiving 1.5k citations

Peers

Jun He
Comparison fields: 5 of 135
  • Experimental and Cognitive Psychology 413
  • Statistics, Probability and Uncertainty 226
  • Computer Vision and Pattern Recognition 553
  • Human-Computer Interaction 100
  • Signal Processing 155
Replace Mauricio A. Álvarez with:
Mauricio A. Álvarez Colombia
Jouko Lampinen Finland
Yassine Ruichek France
Dan Xu China
Maurizio Filippone United Kingdom
Pascal Lamblin Canada
Hao Tang China
Roberto Togneri Australia
Pourya Shamsolmoali China
Xiaoyang Tan China
Jun He relative to Mauricio A. Álvarez Colombia Mauricio A. Álvarez's profile →
Citations per field
00.5×4.1×
Mauricio A. Álvarez · 1×
Citations per year

Countries citing papers authored by Jun He

Since Specialization
Citations

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

Fields of papers citing papers by Jun He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 174 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201480
2 202077
3 200271
4 202364
5 202259
6 201657
7 201754
8 201052
9 201643
10 202142
11 201738
12 201537
13 201835
14 201535
15 201632
16 201730
17 201728
18 201728
19 201427
20 201227

About Jun He

Jun He is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Experimental and Cognitive Psychology, Signal Processing and Civil and Structural Engineering, having authored 174 papers that have together received 1.6k indexed citations. Recurring topics across this work include Emotion and Mood Recognition (26 papers), Face and Expression Recognition (21 papers), Face recognition and analysis (20 papers), Human Pose and Action Recognition (17 papers), Probabilistic and Robust Engineering Design (13 papers), Video Surveillance and Tracking Methods (12 papers), Speech and Audio Processing (11 papers) and Music and Audio Processing (9 papers). The work is most often cited by research in Experimental and Cognitive Psychology (413 citations), Statistics, Probability and Uncertainty (226 citations), Computer Vision and Pattern Recognition (553 citations), Human-Computer Interaction (100 citations) and Signal Processing (155 citations). Jun He has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Bo Sun, Lejun Yu, Jinghai Gong, Liandong Li, Jie Li, Hongyan Liu, Shengbin Gao, Zhaoxin Fan, Xiaoyong Du and Xiaohua Yang. Their work appears in journals such as Structural Safety, Earthquake Engineering and Engineering Vibration, Neurocomputing, Neural Networks and Natural Hazards.

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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