Jaemin Jo

32 papers receiving 499 citations

Peers

Jaemin Jo
Comparison fields: 5 of 108
  • Computer Vision and Pattern Recognition 206
  • Human-Computer Interaction 46
  • Computer Graphics and Computer-Aided Design 16
  • Oncology 97
  • Signal Processing 40
Replace Zhuochen Jin with:
Zhuochen Jin China
Md Baharul Islam Türkiye
Hwan-Seung Yong South Korea
Tong Yu United States
Meihong Wang China
Stephen V. Rice United States
Guangda Li China
Fouad Khelifi United Kingdom
David Squire Australia
Jaemin Jo relative to Zhuochen Jin China Zhuochen Jin's profile →
Citations per field
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Zhuochen Jin · 1×
Citations per year

Countries citing papers authored by Jaemin Jo

Since Specialization
Citations

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

Fields of papers citing papers by Jaemin Jo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jaemin Jo, 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 Jaemin Jo Line = papers co-authored together Jaemin Jo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201378
2 201450
3 201131
4 201329
5 202029
6 201628
7 201727
8 201326
9 202121
10 201819
11 202119
12 201819
13 201517
14 201715
15 202213
16 202312
17 201910
18 20208
19 20198
20 20218

About Jaemin Jo

Jaemin Jo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Sociology and Political Science, having authored 36 papers that have together received 510 indexed citations. Recurring topics across this work include Data Visualization and Analytics (16 papers), Anomaly Detection Techniques and Applications (5 papers), Data Management and Algorithms (4 papers), Video Analysis and Summarization (4 papers), Multimedia Communication and Technology (3 papers), Time Series Analysis and Forecasting (3 papers), Computer Graphics and Visualization Techniques (3 papers) and Green IT and Sustainability (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (206 citations), Human-Computer Interaction (46 citations), Computer Graphics and Computer-Aided Design (16 citations), Oncology (97 citations) and Signal Processing (40 citations). Jaemin Jo has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Jinwook Seo, Sehi L’Yi, Bohyoung Kim, Bongshin Lee, Jean‐Daniel Fekete, Jonghun Park, Kyunghan Lee, Joohyun Lee, Ness B. Shroff and Sin‐Ho Jung. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Annals of Oncology, Visual Informatics, Knowledge-Based Systems and IEEE Access.

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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