Sang-Woo Lee

619 citations
18 papers · 217 indexed · h-index 7
Topics
Topic Modeling (8 papers)Multimodal Machine Learning Applications (6 papers)Natural Language Processing Techniques (5 papers)
Partner nations
South KoreaUnited States

In The Last Decade

Sang-Woo Lee

17 papers receiving 203 citations

Peers

Sang-Woo Lee
Comparison fields: 5 of 58
  • Artificial Intelligence 147
  • Computer Vision and Pattern Recognition 96
  • Economics and Econometrics 28
  • Visual Arts and Performing Arts 23
  • Urban Studies 22
Replace K. Maheswari with:
K. Maheswari India
Amit Pimpalkar India
Geetanjali Garg India
Shauli Ravfogel Israel
Conghui Zhu China
Zhangming Chan China
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Muhammet Sinan Başarslan Türkiye
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Sang-Woo Lee relative to K. Maheswari India K. Maheswari's profile →
Citations per field
00.5×10.3×
K. Maheswari · 1×
Citations per year

Countries citing papers authored by Sang-Woo Lee

Since Specialization
Citations

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

Fields of papers citing papers by Sang-Woo Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sang-Woo Lee

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 1
2 7
3 1
4 3
5 3
6 11
7 2
8 4
9 11
10 0
11
Answerer in Questioner's Mind for Goal-Oriented Visual Dialogue.
3
12 2
13 6
14 120
15
National Wind Atlas Database and Visualization Based on IDL
1
16 18
17 3
18 21

About Sang-Woo Lee

Sang-Woo Lee is a scholar working on Visual Arts and Performing Arts, Urban Studies and Computer Vision and Pattern Recognition, having authored 18 papers that have together received 217 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Multimodal Machine Learning Applications (6 papers) and Natural Language Processing Techniques (5 papers). The work is most often cited by research in Visual Arts and Performing Arts (23 citations), Computer Vision and Pattern Recognition (96 citations) and Artificial Intelligence (147 citations). Sang-Woo Lee has collaborated with scholars based in South Korea and United States. Frequent co-authors include Byoung‐Tak Zhang, Jung-Woo Ha, Jae-Hyun Jun, Jin-Hwa Kim, David Waterman, Sungdong Kim, Minsuk Chang, Dong‐Geol Choi, Jongchan Park and Seung-won Hwang. Their work appears in journals such as Neural Networks, IEEE Robotics and Automation Letters and Electronics.

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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