Tee Connie

2.4k citations
99 papers · 1.5k · h-index 19

Impact in

Papers in

Tee Connie

88 papers receiving 1.4k citations

Peers

Tee Connie
Comparison fields: 5 of 107
  • Signal Processing 1.0k
  • Computer Vision and Pattern Recognition 940
  • Human-Computer Interaction 135
  • Information Systems 537
  • Safety Research 118
Replace Fernando Alonso‐Fernandez with:
Fernando Alonso‐Fernandez Sweden
James L. Wayman United States
Naser Damer Germany
Florian Kirchbuchner Germany
Jang‐Hee Yoo South Korea
Zhe Jin Malaysia
Chih‐Hsien Hsia Taiwan
Annalisa Franco Italy
Saiyed Umer India
Ali Chekima Malaysia
Tee Connie relative to Fernando Alonso‐Fernandez Sweden Fernando Alonso‐Fernandez's profile →
Citations per field
00.5×1.5×
Fernando Alonso‐Fernandez · 1×
Citations per year

Countries citing papers authored by Tee Connie

Since Specialization
Citations

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

Fields of papers citing papers by Tee Connie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 99 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005199
2 2008147
3 2004125
4 201183
5 202073
6
Palmprint Recognition with PCA and ICA
200360
7 201658
8 201039
9 201238
10 200437
11 201034
12 200334
13 201631
14 201024
15 201922
16 201021
17 200920
18 202319
19 200418
20 200617

About Tee Connie

Tee Connie is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Information Systems, Biomedical Engineering and Artificial Intelligence, having authored 99 papers that have together received 1.5k indexed citations. Recurring topics across this work include Biometric Identification and Security (39 papers), Gait Recognition and Analysis (21 papers), User Authentication and Security Systems (17 papers), Human Pose and Action Recognition (15 papers), Hand Gesture Recognition Systems (12 papers), Dermatoglyphics and Human Traits (12 papers), Advanced Steganography and Watermarking Techniques (11 papers) and Anomaly Detection Techniques and Applications (8 papers). The work is most often cited by research in Signal Processing (1.0k citations), Computer Vision and Pattern Recognition (940 citations), Human-Computer Interaction (135 citations), Information Systems (537 citations) and Safety Research (118 citations). Tee Connie has collaborated with scholars based in Malaysia, South Korea and United Kingdom. Frequent co-authors include Andrew Beng Jin Teoh, Michael Kah Ong Goh, Thian Song Ong, David Ngo Chek Ling, David Chek Ling Ngo, Zhe Jin, Cheng-Yaw Low, Pin Shen Teh, Kian Ming Lim and Chin Poo Lee. Their work appears in journals such as IEEE Access, Multimedia Tools and Applications, Pattern Analysis and Applications, Neural Computing and Applications and Neurocomputing.

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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