Jinhee Chun

425 citations
28 papers · 328 · h-index 7

Impact in

Papers in

Jinhee Chun

28 papers receiving 321 citations

Peers

Jinhee Chun
Comparison fields: 5 of 53
  • Computer Graphics and Computer-Aided Design 76
  • Computer Vision and Pattern Recognition 215
  • Experimental and Cognitive Psychology 106
  • Urban Studies 34
  • Human-Computer Interaction 31
Replace Marcelo Bernardes Vieira with:
Marcelo Bernardes Vieira Brazil
Koichiro Niinuma United States
Mahdi Jampour Iran
Simon Dobrišek Slovenia
Yueli Cui China
Zhilong Ji China
Sargur Srihari United States
Sei Naito Japan
Chris Landreth Canada
Jinhee Chun relative to Marcelo Bernardes Vieira Brazil Marcelo Bernardes Vieira's profile →
Citations per field
00.5×10×20×34×
Marcelo Bernardes Vieira · 1×
Citations per year

Countries citing papers authored by Jinhee Chun

Since Specialization
Citations

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

Fields of papers citing papers by Jinhee Chun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019160
2 201634
3 201820
4 200816
5 200415
6 200915
7 20056
8 20076
9 20105
10 20095
11 20035
12 20065
13 20214
14 20104
15 20034
16
Algorithms for computing the maximum weight region decomposable into elementary shapes
20093
17 20173
18 20123
19 20183
20 20053

About Jinhee Chun

Jinhee Chun is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computational Mechanics, Signal Processing and Computer Networks and Communications, having authored 28 papers that have together received 328 indexed citations. Recurring topics across this work include Digital Image Processing Techniques (14 papers), Computational Geometry and Mesh Generation (13 papers), Advanced Numerical Analysis Techniques (7 papers), Medical Image Segmentation Techniques (6 papers), Image Retrieval and Classification Techniques (5 papers), Image Processing and 3D Reconstruction (3 papers), Mathematical Approximation and Integration (2 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (76 citations), Computer Vision and Pattern Recognition (215 citations), Experimental and Cognitive Psychology (106 citations), Urban Studies (34 citations) and Human-Computer Interaction (31 citations). Jinhee Chun has collaborated with scholars based in Japan, Germany and United States. Frequent co-authors include Takeshi Tokuyama, Matias Korman, Martin Nöllenburg, Kunihiko Sadakane, Danny Z. Chen, Naoki Katoh, Yuji Okada, Kohei Asano, Luca Grilli and Fabrizio Montecchiani. Their work appears in journals such as Algorithmica, Theoretical Computer Science, Lecture notes in computer science, Discrete & Computational Geometry and Pattern Recognition Letters.

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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