Sio‐Kei Im

795 citations
119 papers · 446 · h-index 11

Impact in

Papers in

Sio‐Kei Im

90 papers receiving 430 citations

Peers

Sio‐Kei Im
Comparison fields: 5 of 79
  • Signal Processing 107
  • Computer Vision and Pattern Recognition 188
  • Computational Mathematics 3
  • Human-Computer Interaction 19
  • Artificial Intelligence 99
Replace Jagannadan Varadarajan with:
Jagannadan Varadarajan Singapore
Ron van Schyndel Australia
Xiaoming Liu China
Minh-Son Dao Japan
Carlos Ruiz United States
Haojun Ai China
He Feng China
Masatoshi Arikawa Japan
K. Sengupta Singapore
Mansoor Nasir Pakistan
Sio‐Kei Im relative to Jagannadan Varadarajan Singapore Jagannadan Varadarajan's profile →
Citations per field
00.5×10×20×31.3×
Jagannadan Varadarajan · 1×
Citations per year

Countries citing papers authored by Sio‐Kei Im

Since Specialization
Citations

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

Fields of papers citing papers by Sio‐Kei Im

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sio‐Kei Im. 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 Sio‐Kei Im. The network helps show where Sio‐Kei Im may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 119 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201453
2 201846
3 202418
4 202017
5 202314
6 202114
7 202413
8 200513
9 200712
10 202211
11 202010
12 20229
13 20158
14 20247
15 20207
16 20237
17 20207
18 20197
19 20246
20 20236

About Sio‐Kei Im

Sio‐Kei Im is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Electrical and Electronic Engineering and Human-Computer Interaction, having authored 119 papers that have together received 446 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (24 papers), Advanced Vision and Imaging (18 papers), Advanced Data Compression Techniques (16 papers), Topic Modeling (13 papers), Natural Language Processing Techniques (11 papers), Image and Video Quality Assessment (11 papers), Sentiment Analysis and Opinion Mining (7 papers) and Music and Audio Processing (7 papers). The work is most often cited by research in Signal Processing (107 citations), Computer Vision and Pattern Recognition (188 citations), Computational Mathematics (3 citations), Human-Computer Interaction (19 citations) and Artificial Intelligence (99 citations). Sio‐Kei Im has collaborated with scholars based in Macao, China and Portugal. Frequent co-authors include Ka‐Hou Chan, Wei Ke, A.J. Pearmain, Giovanni Pau, Chan‐Tong Lam, Laurie Cuthbert, Yan Zhang, Rita Tse, Xing Zhang and Rong Yu. Their work appears in journals such as IEEE Access, Electronics Letters, Sensors, Applied Sciences and International Journal of Human-Computer Studies.

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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