Jonguk Lee

34 papers receiving 726 citations

Peers

Jonguk Lee
Comparison fields: 5 of 98
  • Small Animals 205
  • Developmental Biology 36
  • Animal Science and Zoology 130
  • Automotive Engineering 148
  • Signal Processing 68
Replace Leonardo L. Giovanini with:
Leonardo L. Giovanini Argentina
Reza Arablouei Australia
Lyndon Smith United Kingdom
Keith A. Ellis Ireland
Kenya Sato Japan
Daihee Park South Korea
Philip Valencia Australia
C.P. Schofield United Kingdom
Dihua Wu China
Jonguk Lee relative to Leonardo L. Giovanini Argentina Leonardo L. Giovanini's profile →
Citations per field
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Leonardo L. Giovanini · 1×
Citations per year

Countries citing papers authored by Jonguk Lee

Since Specialization
Citations

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

Fields of papers citing papers by Jonguk Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013197
2 2016131
3 2016107
4 201389
5 201552
6 202021
7 201717
8 201816
9 201415
10 201812
11 202211
12 201310
13 201710
14 202210
15 20129
16 20245
17 20145
18 20134
19 20174
20
Abnormal Sound Detection and Identification in Surveillance System
20123

About Jonguk Lee

Jonguk Lee is a scholar working on Small Animals, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Signal Processing and Control and Systems Engineering, having authored 45 papers that have together received 753 indexed citations. Recurring topics across this work include Animal Behavior and Welfare Studies (10 papers), Music and Audio Processing (5 papers), Speech and Audio Processing (5 papers), Video Surveillance and Tracking Methods (4 papers), Industrial Vision Systems and Defect Detection (3 papers), Food Supply Chain Traceability (3 papers), Advanced Chemical Sensor Technologies (3 papers) and Electric Vehicles and Infrastructure (3 papers). The work is most often cited by research in Small Animals (205 citations), Developmental Biology (36 citations), Animal Science and Zoology (130 citations), Automotive Engineering (148 citations) and Signal Processing (68 citations). Jonguk Lee has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Daihee Park, Yongwha Chung, Sung‐Kwan Joo, Young-Min Wi, Long Jin, Hong-Hee Chang, Hee‐Young Kim, Suk Kim, Byeongjoon Noh and Manki Min. Their work appears in journals such as Sensors, Symmetry, IEEE Transactions on Consumer Electronics, IEEE Access and Applied 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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