Young-Yoon Lee

1.2k citations
37 papers · 743 · h-index 13

Impact in

Papers in

Young-Yoon Lee

32 papers receiving 710 citations

Peers

Young-Yoon Lee
Comparison fields: 5 of 90
  • Cancer Research 186
  • Computer Vision and Pattern Recognition 252
  • Media Technology 63
  • Signal Processing 61
  • Molecular Biology 300
Replace Dongxiao Li with:
Dongxiao Li China
Cheng‐Han Lin Taiwan
Yongxian Fan China
Weilun Wang China
Jiangwen Sun United States
Renqiang Min Canada
Ronaldo F. Hashimoto Brazil
Daniel Jiménez‐Carretero Spain
Eric Kernfeld United States
Shouhua Wang China
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Citations per field
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Citations per year

Countries citing papers authored by Young-Yoon Lee

Since Specialization
Citations

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

Fields of papers citing papers by Young-Yoon Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011146
2 202373
3 202167
4 202062
5 202358
6 202050
7 202446
8 201939
9 200939
10 202136
11 202118
12 202213
13 200913
14 202011
15 200610
16 200710
17 20048
18 20108
19 20096
20
Order Learning and Its Application to Age Estimation
20205

About Young-Yoon Lee

Young-Yoon Lee is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Molecular Biology, Computer Networks and Communications and Signal Processing, having authored 37 papers that have together received 743 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (8 papers), Digital Media Forensic Detection (6 papers), Advanced Wireless Communication Techniques (5 papers), MicroRNA in disease regulation (5 papers), RNA Research and Splicing (4 papers), PAPR reduction in OFDM (4 papers), Chaos-based Image/Signal Encryption (4 papers) and GNSS positioning and interference (3 papers). The work is most often cited by research in Cancer Research (186 citations), Computer Vision and Pattern Recognition (252 citations), Media Technology (63 citations), Signal Processing (61 citations) and Molecular Biology (300 citations). Young-Yoon Lee has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include V. Narry Kim, Haedong Kim, Chang‐Su Kim, Chul-Woo Lee, Chul Lee, Sang-Uk Lee, Soung‐Hun Roh, Hansol Lee, Munkyong Pae and Dayong Wu. Their work appears in journals such as Molecular Cell, IEEE Transactions on Image Processing, Nature, Nature Reviews Molecular Cell Biology and Journal of Visual Communication and Image Representation.

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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