Minho Lee

3.8k citations
174 papers · 2.3k indexed · h-index 26
Topics
Visual Attention and Saliency Detection (25 papers)Face and Expression Recognition (19 papers)Gaze Tracking and Assistive Technology (18 papers)
Partner nations
South KoreaJapanChina

In The Last Decade

Minho Lee

169 papers receiving 2.2k citations

Peers

Minho Lee
Comparison fields: 5 of 154
  • Computer Vision and Pattern Recognition 748
  • Artificial Intelligence 625
  • Electrical and Electronic Engineering 353
  • Cognitive Neuroscience 328
  • Control and Systems Engineering 227
Replace Xue Wang with:
Xue Wang China
Arpan Pal India
Deepak Ganesan United States
Yongqiang Cheng China
Asha Rani India
Vijander Singh India
Zhi‐Hong Mao United States
Yuan Zhang China
Guoliang Xing United States
Minho Lee relative to Xue Wang China Xue Wang's profile →
Citations per field
00.5×1.5×2.1×
Xue Wang · 1×
Citations per year

Countries citing papers authored by Minho Lee

Since Specialization
Citations

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

Fields of papers citing papers by Minho Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minho Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Minho Lee. A scholar is included among the top collaborators of Minho 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 Minho Lee. Minho 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 1
2 1
3 3
4 7
5 7
6 12
7 2
8 19
9 82
10 75
11 16
12 23
13 14
14 23
15 1
16
Verifications of the low-cost eye-tracker KSL-240
2
17 14
18 15
19 58
20 41

About Minho Lee

Minho Lee is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Cognitive Neuroscience, having authored 174 papers that have together received 2.3k indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (25 papers), Face and Expression Recognition (19 papers) and Gaze Tracking and Assistive Technology (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (748 citations), Human-Computer Interaction (164 citations) and Artificial Intelligence (625 citations). Minho Lee has collaborated with scholars based in South Korea, Japan and China. Frequent co-authors include Rammohan Mallipeddi, Sang-Woo Ban, Amin Jalali, Gil‐Jin Jang, Jihun Kim, Yong-Hwa Choi, Zhibin Yu, Sangwook Kim, Sungmoon Jeong and Hyeung‐Sik Choi. Their work appears in journals such as IEEE Transactions on Industrial Electronics, Applied Energy and Computers in Human Behavior.

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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