John See

5.0k citations
140 papers · 3.4k · 1 hit paper · h-index 31

Impact in

Papers in

John See

131 papers receiving 3.3k citations

John See's Hit Papers

Less is more: Micro-expression recognition from video using apex frame 2017 · 275 citations
2750+3+6Years since publication50100150200250

Peers

John See
Comparison fields: 5 of 121
  • Computer Vision and Pattern Recognition 2.4k
  • Experimental and Cognitive Psychology 1.4k
  • Human-Computer Interaction 443
  • Urban Studies 273
  • Signal Processing 347
Replace Xiaojiang Peng with:
Xiaojiang Peng China
Irene Kotsia United Kingdom
Qirong Mao China
Zhen Cui China
Jiabei Zeng China
Yong Peng China
Qiang Ji United States
Yongzhen Huang China
Thiago Oliveira-Santos Brazil
Junho Yim South Korea
John See relative to Xiaojiang Peng China Xiaojiang Peng's profile →
Citations per field
00.5×1.5×2.2×
Xiaojiang Peng · 1×
Citations per year

Countries citing papers authored by John See

Since Specialization
Citations

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

Fields of papers citing papers by John See

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 140 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Less is more: Micro-expression recognition from video using apex frame
Hit paper breakdown →
2017275
2 2015225
3 2020210
4 2018162
5 2018122
6 2018114
7 2019113
8 2015108
9 202096
10 201994
11 201685
12 201581
13 201579
14 201669
15 201563
16 202063
17 202261
18 201655
19 201652
20 201447

About John See

John See is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Artificial Intelligence, Signal Processing and Cognitive Neuroscience, having authored 140 papers that have together received 3.4k indexed citations. Recurring topics across this work include Face and Expression Recognition (32 papers), Emotion and Mood Recognition (32 papers), Human Pose and Action Recognition (28 papers), Video Surveillance and Tracking Methods (26 papers), Face recognition and analysis (23 papers), Advanced Image and Video Retrieval Techniques (21 papers), Anomaly Detection Techniques and Applications (18 papers) and Advanced Neural Network Applications (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.4k citations), Experimental and Cognitive Psychology (1.4k citations), Human-Computer Interaction (443 citations), Urban Studies (273 citations) and Signal Processing (347 citations). John See has collaborated with scholars based in Malaysia, China and United Kingdom. Frequent co-authors include Raphaël C.‐W. Phan, Weiyao Lin, Sze‐Teng Liong, KokSheik Wong, Anh Cat Le Ngo, Yee-Hui Oh, Yandan Wang, Huai-Qian Khor, Kean Chen and Lai-Kuan Wong. Their work appears in journals such as Signal Processing Image Communication, Neurocomputing, International Journal of Computer Vision, Pattern Recognition Letters and IEEE Transactions on Multimedia.

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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