Pilhyeon Lee

408 total citations
13 papers, 206 citations indexed

About

Pilhyeon Lee is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Pilhyeon Lee has authored 13 papers receiving a total of 206 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 4 papers in Cognitive Neuroscience. Recurrent topics in Pilhyeon Lee's work include Domain Adaptation and Few-Shot Learning (5 papers), Generative Adversarial Networks and Image Synthesis (4 papers) and Multimodal Machine Learning Applications (4 papers). Pilhyeon Lee is often cited by papers focused on Domain Adaptation and Few-Shot Learning (5 papers), Generative Adversarial Networks and Image Synthesis (4 papers) and Multimodal Machine Learning Applications (4 papers). Pilhyeon Lee collaborates with scholars based in South Korea, Canada and China. Pilhyeon Lee's co-authors include Hyeran Byun, Kibeom Hong, Sunhee Hwang, Sungho Park, Dohyung Kim, Dongyoon Wee, Taeoh Kim, Youngjung Uh, Namhyuk Ahn and Junsoo Lee and has published in prestigious journals such as Expert Systems with Applications, Pattern Recognition and Neurocomputing.

In The Last Decade

Pilhyeon Lee

12 papers receiving 201 citations

Peers

Pilhyeon Lee
Comparison fields: 5 of 51
  • Computer Vision and Pattern Recognition 138
  • Artificial Intelligence 119
  • Cognitive Neuroscience 21
  • Signal Processing 15
  • Biomedical Engineering 14
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Saeid Motiian United States
Alessandro Bergamo United States
Dongyoung Kim South Korea
Omar El Farouk Bourahla China
Rosalia Schneider United States
Xuhui Jia United States
Ya-Liang Chang Taiwan
Shuang Ma United States
Gihyun Kwon South Korea
Jinhee Chun Japan
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Citations per field, relative to Pilhyeon Lee
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Citations per year, relative to Pilhyeon Lee
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Countries citing papers authored by Pilhyeon Lee

Since Specialization
Citations

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

Fields of papers citing papers by Pilhyeon Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pilhyeon Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Pilhyeon Lee. A scholar is included among the top collaborators of Pilhyeon Lee 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 Pilhyeon Lee. Pilhyeon Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
# Work Indexed citations
1 5
2 4
3 21
4 0
5 13
6 6
7 17
8 36
9 4
10 6
11 41
12 4
13 49

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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