Minhyeok Lee

2.1k citations
74 papers · 1.1k indexed · 1 hit paper · h-index 18
Topics
Generative Adversarial Networks and Image Synthesis (13 papers)Gene expression and cancer classification (9 papers)Anomaly Detection Techniques and Applications (7 papers)

In The Last Decade

Minhyeok Lee

67 papers receiving 1.1k citations

Hit Papers

Hierarchically Decomposed Graph Convolutional Networks fo...202320262024202520234080120

Peers

Minhyeok Lee
Comparison fields: 5 of 138
  • Computer Vision and Pattern Recognition 408
  • Artificial Intelligence 302
  • Biomedical Engineering 196
  • Molecular Biology 190
  • Radiology, Nuclear Medicine and Imaging 82
Replace Qingqi Hong with:
Qingqi Hong China
Issei Sato Japan
Qihang Zhang China
Lia Morra Italy
Mohammad Azzeh Jordan
Quan Liu China
Hakil Kim South Korea
Donglai Wei United States
Naveed Islam Pakistan
Lei Cui China
Minhyeok Lee relative to Qingqi Hong China Qingqi Hong's profile →
Citations per field
00.5×3.5×
Qingqi Hong · 1×
Citations per year

Countries citing papers authored by Minhyeok Lee

Since Specialization
Citations

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

Fields of papers citing papers by Minhyeok Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minhyeok Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Minhyeok Lee. A scholar is included among the top collaborators of Minhyeok 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 Minhyeok Lee. Minhyeok Lee 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 2
2 0
3 6
4 3
5 9
6 10
7 17
8 12
9 52
10 7
11 39
12 1
13 94
14 53
15 13
16 20
17 6
18 11
19 9
20 13

About Minhyeok Lee

Minhyeok Lee is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 74 papers that have together received 1.1k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (13 papers), Gene expression and cancer classification (9 papers) and Anomaly Detection Techniques and Applications (7 papers). The work is most often cited by research in Health Informatics (31 citations), Computer Vision and Pattern Recognition (408 citations) and Artificial Intelligence (302 citations). Minhyeok Lee has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Junhee Seok, Sangyoun Lee, Dogyoon Lee, Suhwan Cho, Chaewon Park, Seunghoon Lee, In-Soo Kim, Jae Sang Heo, Seong Hyun Kim and Jee Young Kwak. Their work appears in journals such as Advanced Materials, Bioinformatics and PLoS ONE.

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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