Eva Cheng

708 citations
62 papers · 499 · h-index 13

Impact in

Papers in

Eva Cheng

54 papers receiving 478 citations

Peers

Eva Cheng
Comparison fields: 5 of 99
  • Computer Vision and Pattern Recognition 202
  • Signal Processing 84
  • Human-Computer Interaction 36
  • Media Technology 57
  • Computer Science Applications 23
Replace Geneviève Patterson with:
Geneviève Patterson United States
Bing Zhou China
Anastasis Kounoudes Greece
Eric Haines United States
Sinan Kalkan Türkiye
Zoe Falomir Germany
Songfan Yang United States
Lan Ma China
Weifeng Ge China
Eva Cheng relative to Geneviève Patterson United States Geneviève Patterson's profile →
Citations per field
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Geneviève Patterson · 1×
Citations per year

Countries citing papers authored by Eva Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Eva Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201653
2 201646
3 201241
4 201234
5 201127
6 201625
7 201720
8 200518
9 202217
10 202015
11 201115
12 201614
13 201712
14 202111
15 201611
16 201510
17 20228
18 20177
19 20127
20 20187

About Eva Cheng

Eva Cheng is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Signal Processing, Biomedical Engineering and Aerospace Engineering, having authored 62 papers that have together received 499 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (11 papers), Speech and Audio Processing (10 papers), Acoustic Wave Phenomena Research (8 papers), Hearing Loss and Rehabilitation (7 papers), Noise Effects and Management (6 papers), Advanced Adaptive Filtering Techniques (5 papers), Robotics and Sensor-Based Localization (5 papers) and Wind and Air Flow Studies (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (202 citations), Signal Processing (84 citations), Human-Computer Interaction (36 citations), Media Technology (57 citations) and Computer Science Applications (23 citations). Eva Cheng has collaborated with scholars based in Australia, Taiwan and Vietnam. Frequent co-authors include Lee Burnett, Margaret Lech, Sipei Zhao, Xiaojun Qiu, Christian Ritz, Margaret Hamilton, Flora D. Salim, Suelynn Choy, Stephen J. Davis and Stuart Perry. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Access, Scientific Reports, Electronics and Architectural Science Review.

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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