Youngwan Lee

890 citations
30 papers · 605 · 1 hit paper · h-index 11

Impact in

Papers in

Youngwan Lee

28 papers receiving 586 citations

Youngwan Lee's Hit Papers

MPViT: Multi-Path Vision Transformer for Dense Prediction 2022 · 265 citations
2650+1+2Years since publication50100150200250

Peers

Youngwan Lee
Comparison fields: 5 of 76
  • Computer Vision and Pattern Recognition 321
  • Media Technology 96
  • Polymers and Plastics 66
  • Automotive Engineering 40
  • Industrial and Manufacturing Engineering 32
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Youngwan Lee relative to Anran Wang China Anran Wang's profile →
Citations per field
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Anran Wang · 1×
Citations per year

Countries citing papers authored by Youngwan Lee

Since Specialization
Citations

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

Fields of papers citing papers by Youngwan Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Youngwan Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Youngwan Lee Line = papers co-authored together Youngwan Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
MPViT: Multi-Path Vision Transformer for Dense Prediction
Hit paper breakdown →
2022265
2 202152
3 201641
4 202434
5 201731
6 202229
7 202015
8 201614
9 202313
10 201611
11 201911
12 202111
13 202510
14 20218
15 20168
16 20178
17 20216
18 20246
19 20206
20 20166

About Youngwan Lee

Youngwan Lee is a scholar working on Computer Vision and Pattern Recognition, Polymers and Plastics, Artificial Intelligence, Industrial and Manufacturing Engineering and Automotive Engineering, having authored 30 papers that have together received 605 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (9 papers), Video Surveillance and Tracking Methods (8 papers), Conducting polymers and applications (6 papers), Autonomous Vehicle Technology and Safety (4 papers), Organic Electronics and Photovoltaics (4 papers), Industrial Vision Systems and Defect Detection (4 papers), Human Pose and Action Recognition (3 papers) and GaN-based semiconductor devices and materials (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (321 citations), Media Technology (96 citations), Polymers and Plastics (66 citations), Automotive Engineering (40 citations) and Industrial and Manufacturing Engineering (32 citations). Youngwan Lee has collaborated with scholars based in South Korea, Pakistan and United States. Frequent co-authors include Sung Ju Hwang, Jonghee Kim, Hakil Kim, Eunsoo H Park, Jongyoul Park, BongSoo Kim, Xuenan Cui, Peddaboodi Gopikrishna, Hyung-Il Kim and Shinuk Cho. Their work appears in journals such as Advanced Optical Materials, IEEE Access, IEEE Transactions on Broadcasting, ACS Applied Energy Materials and ACS Applied Materials & Interfaces.

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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