In-Kwon Yeo

2.0k citations
23 papers · 1.3k indexed · 1 hit paper · h-index 7
Topics
Statistical Methods and Inference (7 papers)Advanced Steganography and Watermarking Techniques (5 papers)Digital Media Forensic Detection (4 papers)
Partner nations
South KoreaUnited States

In The Last Decade

In-Kwon Yeo

17 papers receiving 1.2k citations

Hit Papers

A new family of power transformations to improve normalit...200020262008201720002505007501000

Peers

In-Kwon Yeo
Comparison fields: 5 of 175
  • Computer Vision and Pattern Recognition 235
  • Artificial Intelligence 181
  • Statistics and Probability 161
  • Global and Planetary Change 133
  • Signal Processing 83
Replace David N. Reshef with:
David N. Reshef United States
Ray D. Nelson United States
Wendy L. Martinez United States
C. Spearman
Cheolwoo Park South Korea
Bertrand Michel France
Nicola L. C. Talbot United Kingdom
Feng Liang United States
Allan Seheult United Kingdom
Charles L. Dunn United States
In-Kwon Yeo relative to David N. Reshef United States David N. Reshef's profile →
Citations per field
00.5×1.5×
David N. Reshef · 1×
Citations per year

Countries citing papers authored by In-Kwon Yeo

Since Specialization
Citations

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

Fields of papers citing papers by In-Kwon Yeo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by In-Kwon Yeo. 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 In-Kwon Yeo. The network helps show where In-Kwon Yeo may publish in the future.

Co-authorship network of co-authors of In-Kwon Yeo

This figure shows the co-authorship network connecting the top 25 collaborators of In-Kwon Yeo. A scholar is included among the top collaborators of In-Kwon Yeo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with In-Kwon Yeo. In-Kwon Yeo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 2
3 0
4
Statistical Analysis on Sentencing Factor and Its Rationality
1
5 0
6 1
7 0
8 4
9 0
10 7
11 6
12 4
13
Generalized patchwork algorithm for image watermarking
4
14 141
15 33
16 1
17 26
18 7
19 6
20 10

About In-Kwon Yeo

In-Kwon Yeo is a scholar working on Statistics and Probability, Management Science and Operations Research and Finance, having authored 23 papers that have together received 1.3k indexed citations. Recurring topics across this work include Statistical Methods and Inference (7 papers), Advanced Steganography and Watermarking Techniques (5 papers) and Digital Media Forensic Detection (4 papers). The work is most often cited by research in Statistics and Probability (161 citations), Computer Vision and Pattern Recognition (235 citations) and Signal Processing (83 citations). In-Kwon Yeo has collaborated with scholars based in South Korea and United States. Frequent co-authors include Hyoung Joong Kim, Hyoung Joong Kim, Richard A. Johnson, Wei‐Yin Loh, Sun Young Hwang, I. V. Basawa, Dong Ho Park, Dae Kyung Kim, Tae-Hoon Kim and Young‐Geun Choi. Their work appears in journals such as Biometrika, IEEE Transactions on Speech and Audio Processing and Multimedia Systems.

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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