Ching-Chung Li

988 citations
56 papers · 662 · h-index 13

Impact in

Papers in

Ching-Chung Li

52 papers receiving 583 citations

Peers

Ching-Chung Li
Comparison fields: 5 of 90
  • Computer Vision and Pattern Recognition 429
  • Signal Processing 150
  • Experimental and Cognitive Psychology 153
  • Media Technology 65
  • Human-Computer Interaction 33
Replace Çiğdem Eroğlu Erdem with:
Çiğdem Eroğlu Erdem Türkiye
Yingyong Qi United States
Alaa Eleyan Türkiye
Xavier Binefa Spain
A. Tanju Erdem United States
José M. Buenaposada Spain
Eric Haines United States
Yun Tie China
Xiaodan Zhuang United States
Ching-Chung Li relative to Çiğdem Eroğlu Erdem Türkiye Çiğdem Eroğlu Erdem's profile →
Citations per field
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Çiğdem Eroğlu Erdem · 1×
Citations per year

Countries citing papers authored by Ching-Chung Li

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Chung Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Chung Li. 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 Ching-Chung Li. The network helps show where Ching-Chung Li may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002142
2 200065
3
Automatic recognition of facial expressions using hidden markov models and estimation of expression intensity
199859
4 200255
5 200751
6 199835
7 199532
8 200920
9 200317
10 201114
11 200214
12 200213
13 200712
14 200410
15 20088
16 20057
17 20056
18 20056
19 20096
20 20066

About Ching-Chung Li

Ching-Chung Li is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Biomedical Engineering, Media Technology and Artificial Intelligence, having authored 56 papers that have together received 662 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (25 papers), Advanced Image Fusion Techniques (11 papers), Advanced Data Compression Techniques (11 papers), Speech and Audio Processing (10 papers), Hearing Loss and Rehabilitation (9 papers), Acoustic Wave Phenomena Research (6 papers), Medical Image Segmentation Techniques (5 papers) and Face and Expression Recognition (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (429 citations), Signal Processing (150 citations), Experimental and Cognitive Psychology (153 citations), Media Technology (65 citations) and Human-Computer Interaction (33 citations). Ching-Chung Li has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Takeo Kanade, Jeffrey F. Cohn, Jenn-Jier James Lien, Robert J. Sclabassi, Mingui Sun, James Miller, Yu‐Te Wu, J.R. Boston, John D. Durrant and Hsi‐Chin Hsin. Their work appears in journals such as Pattern Recognition Letters, The Journal of the Acoustical Society of America, International Journal of Computer Vision, Optics Letters and Terrestrial Atmospheric and Oceanic Sciences.

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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