Young-Seol Lee

475 citations
15 papers · 138 indexed · h-index 6
Co-authors
Sung‐Bae Cho
Topics
Context-Aware Activity Recognition Systems (7 papers)Video Analysis and Summarization (6 papers)Multimedia Communication and Technology (3 papers)
Journals
SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsNeurocomputing
Partner nations
South Korea

In The Last Decade

Young-Seol Lee

15 papers receiving 129 citations

Peers

Young-Seol Lee
Comparison fields: 5 of 51
  • Computer Vision and Pattern Recognition 92
  • Artificial Intelligence 49
  • Computer Networks and Communications 26
  • Transportation 23
  • Biomedical Engineering 17
Replace Joy Lal Sarkar with:
Joy Lal Sarkar India
Yves Vanrompay Belgium
Martin Strohbach Germany
Przemyslaw Woznowski United Kingdom
Pedro Chahuara France
Amal El Fallah-Seghrouchni France
Ahmed Salem United States
Bruno Castro da Silva United States
Edson dos Santos Moreira Brazil
Raghubir Singh United Kingdom
Young-Seol Lee relative to Joy Lal Sarkar India Joy Lal Sarkar's profile →
Citations per field
00.5×2.8×
Joy Lal Sarkar · 1×
Citations per year

Countries citing papers authored by Young-Seol Lee

Since Specialization
Citations

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

Fields of papers citing papers by Young-Seol Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Young-Seol Lee

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

All Works

15 of 15 papers shown
#WorkIndexed citations
1 10
2 4
3 1
4 56
5 7
6 1
7 3
8 3
9 5
10 5
11 5
12 14
13 10
14 3
15 11

About Young-Seol Lee

Young-Seol Lee is a scholar working on Computer Vision and Pattern Recognition, Transportation and Signal Processing, having authored 15 papers that have together received 138 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (7 papers), Video Analysis and Summarization (6 papers) and Multimedia Communication and Technology (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (92 citations), Transportation (23 citations) and Artificial Intelligence (49 citations). Young-Seol Lee has collaborated with scholars based in South Korea. Frequent co-authors include Sung‐Bae Cho. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Neurocomputing.

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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