Jae-Hak Kim

870 citations
45 papers · 705 · h-index 15

Impact in

Papers in

Jae-Hak Kim

42 papers receiving 680 citations

Peers

Jae-Hak Kim
Comparison fields: 5 of 88
  • Computer Vision and Pattern Recognition 322
  • Aerospace Engineering 332
  • Geology 33
  • Inorganic Chemistry 77
  • Computer Graphics and Computer-Aided Design 16
Replace Guoxian Dai with:
Guoxian Dai United States
Johan Forsberg Sweden
Jiren Liu China
Robert D. Mariani United States
Stefano Cattini Italy
Xuexue Zhang China
Boliang Wang China
Zhikang Yuan China
Sebastian Kluge Germany
Jinsong Zhang Canada
Jae-Hak Kim relative to Guoxian Dai United States Guoxian Dai's profile →
Citations per field
00.5×6.4×
Guoxian Dai · 1×
Citations per year

Countries citing papers authored by Jae-Hak Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jae-Hak Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae-Hak Kim. 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 Jae-Hak Kim. The network helps show where Jae-Hak Kim may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200896
2 200161
3 200855
4 200948
5 200143
6 201343
7 199741
8 201438
9 200937
10 200735
11 201629
12 199724
13 199620
14 200818
15 200114
16 201214
17 199913
18 20058
19 19988
20
Numerical Study on the Natural Circulation Characteristics in an Integral Type Marine Reactor for Inclined Conditions
20017

About Jae-Hak Kim

Jae-Hak Kim is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Electrical and Electronic Engineering, Radiology, Nuclear Medicine and Imaging and Mechanical Engineering, having authored 45 papers that have together received 705 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (10 papers), Robotics and Sensor-Based Localization (10 papers), Advanced Image and Video Retrieval Techniques (6 papers), Boron Compounds in Chemistry (5 papers), Radiopharmaceutical Chemistry and Applications (5 papers), Nuclear reactor physics and engineering (4 papers), Welding Techniques and Residual Stresses (3 papers) and Engineering Applied Research (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (322 citations), Aerospace Engineering (332 citations), Geology (33 citations), Inorganic Chemistry (77 citations) and Computer Graphics and Computer-Aided Design (16 citations). Jae-Hak Kim has collaborated with scholars based in South Korea, Australia and United States. Frequent co-authors include Richard Hartley, Hongdong Li, Youngkyu Do, Jan‐Michael Frahm, Marc Pollefeys, Goon-Cherl Park, Taewan Kim, Sangmin Lee, Adrien Bartoli and Jeong‐Wook Hwang. Their work appears in journals such as Inorganica Chimica Acta, IEEE Transactions on Pattern Analysis and Machine Intelligence, Nuclear Technology, Inorganic Chemistry and The Journal of Antibiotics.

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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