Jae-Hak Kim

866 citations
43 papers · 611 · h-index 14

Impact in

Papers in

Jae-Hak Kim

39 papers receiving 587 citations

Peers

Jae-Hak Kim
Comparison fields: 5 of 85
  • Computer Vision and Pattern Recognition 257
  • Aerospace Engineering 273
  • Inorganic Chemistry 72
  • Geology 27
  • Electronic, Optical and Magnetic Materials 70
Replace Stefano Cattini with:
Stefano Cattini Italy
Xuexue Zhang China
Robert D. Mariani United States
Jingjun Wu China
Rohan Sawhney United States
Jinsong Zhang Canada
Sen Li China
Jinchuan Wang China
Zhuo Zeng China
Zhikang Yuan China
Jae-Hak Kim relative to Stefano Cattini Italy Stefano Cattini's profile →
Citations per field
00.5×10×13.7×
Stefano Cattini · 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 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200888
2 200160
3 200851
4 200944
5 200143
6 199740
7 201338
8 201437
9 200935
10 201627
11 199721
12 199618
13 200815
14 199913
15 200110
16 19988
17 20058
18
Numerical Study on the Natural Circulation Characteristics in an Integral Type Marine Reactor for Inclined Conditions
20017
19 20136
20 20076

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 43 papers that have together received 611 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (9 papers), Robotics and Sensor-Based Localization (8 papers), Boron Compounds in Chemistry (5 papers), Radiopharmaceutical Chemistry and Applications (5 papers), Nuclear reactor physics and engineering (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Electric Motor Design and Analysis (3 papers) and Sensorless Control of Electric Motors (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (257 citations), Aerospace Engineering (273 citations), Inorganic Chemistry (72 citations), Geology (27 citations) and Electronic, Optical and Magnetic Materials (70 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, Goon-Cherl Park, Sangmin Lee, Taewan Kim, Jeong‐Wook Hwang, Ian Reid, Adrien Bartoli and Marc Pollefeys. Their work appears in journals such as Nuclear Technology, Inorganica Chimica Acta, IEEE Transactions on Pattern Analysis and Machine Intelligence, Inorganic Chemistry and Nuclear Engineering and Technology.

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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