Doo-chul Choi

20 total papers · 448 total citations
19 papers, 373 citations indexed

About

Doo-chul Choi is a scholar working on Industrial and Manufacturing Engineering, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Doo-chul Choi has authored 19 papers receiving a total of 373 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Industrial and Manufacturing Engineering, 10 papers in Computational Mechanics and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Doo-chul Choi's work include Industrial Vision Systems and Defect Detection (16 papers), Surface Roughness and Optical Measurements (9 papers) and Image and Object Detection Techniques (5 papers). Doo-chul Choi is often cited by papers focused on Industrial Vision Systems and Defect Detection (16 papers), Surface Roughness and Optical Measurements (9 papers) and Image and Object Detection Techniques (5 papers). Doo-chul Choi collaborates with scholars based in South Korea. Doo-chul Choi's co-authors include Yong-Ju Jeon, Sang Woo Kim, Jong Pil Yun, Sang Jun Lee, Chang‐Hyun Park, Sang Jun Lee, Seokbae Moon, Jewon Lee, Seung‐Hun Kim and Hyeonwoo Cho and has published in prestigious journals such as Journal of the Optical Society of America A, The International Journal of Advanced Manufacturing Technology and ISIJ International.

In The Last Decade

Doo-chul Choi

19 papers receiving 352 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Doo-chul Choi 304 152 145 99 81 19 373
Nirbhar Neogi 279 0.9× 122 0.8× 140 1.0× 153 1.5× 76 0.9× 11 405
Ying Tian 332 1.1× 111 0.7× 174 1.2× 135 1.4× 81 1.0× 29 396
Shuanlong Niu 251 0.8× 67 0.4× 139 1.0× 114 1.2× 70 0.9× 14 385
Dan Li 223 0.7× 59 0.4× 173 1.2× 89 0.9× 67 0.8× 27 360
Gabriel Fricout 219 0.7× 87 0.6× 117 0.8× 117 1.2× 56 0.7× 16 393
Marcello Chiurazzi 203 0.7× 54 0.4× 117 0.8× 73 0.7× 56 0.7× 14 423
Matti Niskanen 134 0.4× 52 0.3× 186 1.3× 30 0.3× 20 0.2× 20 360
Wei‐Yao Chiu 244 0.8× 58 0.4× 221 1.5× 42 0.4× 31 0.4× 25 427
Junfeng Jing 223 0.7× 66 0.4× 149 1.0× 29 0.3× 64 0.8× 34 354
Shih-Chieh Wu 219 0.7× 32 0.2× 119 0.8× 35 0.4× 22 0.3× 14 396

Countries citing papers authored by Doo-chul Choi

Since Specialization
Citations

This map shows the geographic impact of Doo-chul 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-chul 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-chul Choi more than expected).

Fields of papers citing papers by Doo-chul Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Doo-chul Choi

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

All Works

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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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