John See

5.4k citations
149 papers · 4.0k · 1 hit paper · h-index 33

Impact in

Papers in

John See

138 papers receiving 3.9k citations

John See's Hit Papers

Less is more: Micro-expression recognition from video using apex frame 2017 · 306 citations
3060+3+6Years since publication100200300

Peers

John See
Comparison fields: 5 of 54
  • Experimental and Cognitive Psychology 2.1k
  • Computer Vision and Pattern Recognition 1.1k
  • Human-Computer Interaction 22
  • Industrial and Manufacturing Engineering 32
  • Artificial Intelligence 88
Replace Dong‐Hyun Lee with:
Dong‐Hyun Lee South Korea
Xiaojiang Peng China
Chuang Zhang China
Weifeng Ge China
Zhong Yin China
Kamal Nasrollahi Denmark
Anbang Yao China
Zhigang Zhu United States
Kaihao Zhang China
John See relative to Dong‐Hyun Lee South Korea Dong‐Hyun Lee's profile →
Citations per field
00.5×2×3×4×4.6×
Dong‐Hyun Lee · 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 149 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 →
2017306
2 2015235
3 2020234
4 2018180
5 2019178
6 2019137
7 2018135
8 2018123
9 2019122
10 2015114
11 2019106
12 2020102
13 201588
14 201683
15 201581
16 201673
17 202066
18 202264
19 201563
20 201655

About John See

John See is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Signal Processing, Industrial and Manufacturing Engineering and Human-Computer Interaction, having authored 149 papers that have together received 4.0k indexed citations. Recurring topics across this work include Emotion and Mood Recognition (36 papers), Human Pose and Action Recognition (16 papers), Advanced Neural Network Applications (11 papers), Video Surveillance and Tracking Methods (9 papers), Face and Expression Recognition (7 papers), Image and Video Quality Assessment (4 papers), Face recognition and analysis (3 papers) and Industrial Vision Systems and Defect Detection (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (2.1k citations), Computer Vision and Pattern Recognition (1.1k citations), Human-Computer Interaction (22 citations), Industrial and Manufacturing Engineering (32 citations) and Artificial Intelligence (88 citations). John See has collaborated with scholars based in Malaysia, China and United Kingdom. Frequent co-authors include Raphaël C.‐W. Phan, Weiyao Lin, Yee-Hui Oh, Sze‐Teng Liong, Wong KokSheik, Anh Cat Le Ngo, Yandan Wang, Huai-Qian Khor, Kean Chen and Moi Hoon Yap. Their work appears in journals such as Signal Processing Image Communication, Neurocomputing, IEEE Transactions on Image Processing, IEEE Transactions on Pattern Analysis and Machine Intelligence and ACM Transactions on Multimedia Computing Communications and Applications.

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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