Doo-Hyun Choi

1.4k citations
85 papers · 1.0k indexed · h-index 19

Doo-Hyun Choi

75 papers receiving 940 citations

Peers

Doo-Hyun Choi
Comparison fields: 5 of 81
  • Media Technology 165
  • Computer Vision and Pattern Recognition 330
  • Ceramics and Composites 88
  • Industrial and Manufacturing Engineering 138
  • Materials Chemistry 299
Replace Kei Sakaguchi with:
Kei Sakaguchi Japan
Haiyong Chen China
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Doo-Hyun Choi relative to Kei Sakaguchi Japan Kei Sakaguchi's profile →
Citations per field
00.5×4.2×
Kei Sakaguchi · 1×
Citations per year

Countries citing papers authored by Doo-Hyun Choi

Since Specialization
Citations

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

Fields of papers citing papers by Doo-Hyun Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Doo-Hyun Choi. 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 Doo-Hyun Choi. The network helps show where Doo-Hyun Choi may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20241
3 20240
4 20241
5 20232
6 20210
7 20205
8 201925
9 201935
10 20189
11 20183
12 20134
13
Performance Comparison of Pipeline Defects' Length Estimation Using MFL Signals
20091
14
Image Reconstruction Using Line-scan Image for LCD Surface Inspection
20041
15 200418
16 20011
17
A New Fast Evolutionary Programming Algorithm for Continuous Function Optimization.
19991
18 199810
19
Connectionist-nonconnectionist fusion architecture for high speed road following
19962
20
Nonlinear camera calibration using neural networks
19946

About Doo-Hyun Choi

Doo-Hyun Choi is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Ceramics and Composites, having authored 85 papers that have together received 1.0k indexed citations. Recurring topics across this work include Vehicle License Plate Recognition (9 papers), Metaheuristic Optimization Algorithms Research (8 papers), Industrial Vision Systems and Defect Detection (8 papers), Evolutionary Algorithms and Applications (7 papers), Ferroelectric and Piezoelectric Materials (7 papers), Advanced ceramic materials synthesis (6 papers), Microwave Dielectric Ceramics Synthesis (6 papers) and Non-Destructive Testing Techniques (6 papers). The work is most often cited by research in Media Technology (165 citations), Computer Vision and Pattern Recognition (330 citations) and Ceramics and Composites (88 citations). Doo-Hyun Choi has collaborated with scholars based in South Korea, United States and Poland. Frequent co-authors include Michael T. Lanagan, Kwang‐Ju Kim, Se‐Young Oh, Pyong-Kun Kim, Yun-Su Chung, Young‐Chul Song, Clive A. Randall, Ick Hoon Jang, Nam Chul Kim and Mi Hye Kim. Their work appears in journals such as Journal of Applied Physics, Journal of the American Ceramic Society and Expert Systems with Applications.

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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