Seungho Lee

956 citations
27 papers · 481 indexed · h-index 10
Topics
Advanced Neural Network Applications (5 papers)Robotic Path Planning Algorithms (4 papers)Simulation Techniques and Applications (4 papers)

In The Last Decade

Seungho Lee

22 papers receiving 468 citations

Peers

Seungho Lee
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 209
  • Automotive Engineering 116
  • Control and Systems Engineering 108
  • Artificial Intelligence 108
  • Aerospace Engineering 40
Replace Xiangmin Guan with:
Xiangmin Guan China
Joseph Rios United States
Young-Guk Ha South Korea
Wenjiang Ji China
Fatma Outay United Arab Emirates
Natasha Neogi United States
Sanjiv Sharma United Kingdom
Shangding Gu China
Wenqiang Xu China
Louahdi Khoudour France
Seungho Lee relative to Xiangmin Guan China Xiangmin Guan's profile →
Citations per field
00.5×1.6×
Xiangmin Guan · 1×
Citations per year

Countries citing papers authored by Seungho Lee

Since Specialization
Citations

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

Fields of papers citing papers by Seungho Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seungho Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Seungho Lee. A scholar is included among the top collaborators of Seungho 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 Seungho Lee. Seungho 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 0
2 0
3 3
4 14
5 8
6 11
7 2
8 25
9 78
10
Residual CNN-based Image Super-Resolution for CT Slice Thickness Reduction using Paired CT Scans : Preliminary Validation Study
2
11 3
12 152
13 32
14 0
15
Segment-based land Cover Classification using Texture Information in Degraded Forest land of North Korea
4
16 42
17 44
18 5
19
A Study on Measurement of Rock Slope Joint using 3D Image Processing
1
20 31

About Seungho Lee

Seungho Lee is a scholar working on Computer Vision and Pattern Recognition, General Decision Sciences and Management Science and Operations Research, having authored 27 papers that have together received 481 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Robotic Path Planning Algorithms (4 papers) and Simulation Techniques and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (209 citations), Automotive Engineering (116 citations) and Control and Systems Engineering (108 citations). Seungho Lee has collaborated with scholars based in South Korea, United States and Luxembourg. Frequent co-authors include H. Eric Tseng, Scott Varnhagen, Chang Liu, Hyunjung Shim, Junsuk Choe, Young‐Jun Son, Teresa M. Adams, Karthik Vasudevan, Nurçin Çelik and Jangwon Suh. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Technometrics and Radiology.

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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