Yuk‐Hee Chan

1.3k citations
104 papers · 854 · h-index 15

Impact in

Papers in

Yuk‐Hee Chan

93 papers receiving 791 citations

Peers

Yuk‐Hee Chan
Comparison fields: 5 of 74
  • Computer Vision and Pattern Recognition 675
  • Media Technology 196
  • Signal Processing 204
  • Computer Graphics and Computer-Aided Design 26
  • Acoustics and Ultrasonics 5
Replace R.J. Safranek with:
R.J. Safranek United States
I. Sebestyén Austria
R.D. Dony Canada
L. Torres Spain
J.-R. Ohm Germany
Mohiy M. Hadhoud Egypt
Patrick Hanrahan United States
Dongbo Min South Korea
Minghui Wang China
Bengt J. Nilsson Sweden
Yuk‐Hee Chan relative to R.J. Safranek United States R.J. Safranek's profile →
Citations per field
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R.J. Safranek · 1×
Citations per year

Countries citing papers authored by Yuk‐Hee Chan

Since Specialization
Citations

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

Fields of papers citing papers by Yuk‐Hee Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yuk‐Hee Chan. 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 Yuk‐Hee Chan. The network helps show where Yuk‐Hee Chan may publish in the future.

Co-authors

The 23 scholars most cited alongside Yuk‐Hee Chan, 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 Yuk‐Hee Chan Line = papers co-authored together Yuk‐Hee Chan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 104 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006141
2 199263
3 200850
4 202033
5 199328
6 199727
7 201825
8 200423
9 201822
10 199422
11 200719
12 199818
13 200415
14 201915
15 199114
16 201614
17 200613
18 201313
19 199212
20 201011

About Yuk‐Hee Chan

Yuk‐Hee Chan is a scholar working on Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics, Signal Processing, Media Technology and Electrical and Electronic Engineering, having authored 104 papers that have together received 854 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (46 papers), Image Enhancement Techniques (37 papers), Color Science and Applications (30 papers), Advanced Image Processing Techniques (27 papers), Advanced Data Compression Techniques (20 papers), Digital Filter Design and Implementation (16 papers), Image and Video Quality Assessment (10 papers) and Advanced Vision and Imaging (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (675 citations), Media Technology (196 citations), Signal Processing (204 citations), Computer Graphics and Computer-Aided Design (26 citations) and Acoustics and Ultrasonics (5 citations). Yuk‐Hee Chan has collaborated with scholars based in Hong Kong, China and Canada. Frequent co-authors include Wan-Chi Siu, K.‐H. Chung, Daniel Pak-Kong Lun, Wan-Chi Siu, W.C. Siu, Sheung‐On Choy, Lap‐Pui Chau, Mei Yu, Tai-Chiu Hsung and Kwok-Tung Lo. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Signal Processing Letters, Signal Processing Image Communication and Electronics Letters.

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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