Jaekoo Lee

612 total citations
39 papers, 398 citations indexed

About

Jaekoo Lee is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Jaekoo Lee has authored 39 papers receiving a total of 398 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 6 papers in Molecular Biology and 6 papers in Artificial Intelligence. Recurrent topics in Jaekoo Lee's work include Enzyme Production and Characterization (5 papers), Education and Learning Interventions (4 papers) and Phytase and its Applications (4 papers). Jaekoo Lee is often cited by papers focused on Enzyme Production and Characterization (5 papers), Education and Learning Interventions (4 papers) and Phytase and its Applications (4 papers). Jaekoo Lee collaborates with scholars based in South Korea and United States. Jaekoo Lee's co-authors include Daehee Kim, Youngjun Yoo, Jinkyu Kim, Seunghyun Park, Sunyoung Kwon, Ki‐Jun Park, Byung Yong Kang, Jaiesoon Cho, Sungroh Yoon and Hyunjae Kim and has published in prestigious journals such as IEEE Access, Sensors and IEEE Transactions on Communications.

In The Last Decade

Jaekoo Lee

27 papers receiving 378 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jaekoo Lee South Korea 8 153 92 53 52 49 39 398
Xingang Yu China 9 89 0.6× 24 0.3× 26 0.5× 8 0.2× 7 0.1× 25 444
Stephen A. Ward United States 12 38 0.2× 46 0.5× 25 0.5× 8 0.2× 7 0.1× 18 369
Pedro Carvalho Portugal 9 26 0.2× 87 0.9× 17 0.3× 15 0.3× 4 0.1× 42 284
Nan Bao China 11 29 0.2× 56 0.6× 81 1.5× 47 1.0× 34 315
João M. O. S. Rodrigues Portugal 11 49 0.3× 22 0.2× 58 1.1× 29 0.6× 5 0.1× 45 391
Sion Hannuna United Kingdom 9 18 0.1× 131 1.4× 34 0.6× 18 0.3× 2 0.0× 20 274
Huiqian Wang China 9 43 0.3× 107 1.2× 29 0.5× 11 0.2× 23 310
J. Tsay United States 9 20 0.1× 56 0.6× 108 2.0× 1 0.0× 30 0.6× 15 317
Linghan Zhang China 13 178 1.2× 116 1.3× 75 1.4× 1 0.0× 4 0.1× 33 675

Countries citing papers authored by Jaekoo Lee

Since Specialization
Citations

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

Fields of papers citing papers by Jaekoo Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaekoo Lee

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

All Works

20 of 20 papers shown
1.
Lee, Gilwon, et al.. (2025). Deep Sequential Feature Learning for Phase Noise Compensation in Sub-THz Systems. IEEE Transactions on Communications. 73(9). 7568–7583.
2.
Lee, Jaekoo, et al.. (2022). Deep learning-based direction finding in the presence of direction-dependent mutual coupling. ICT Express. 9(4). 670–676. 1 indexed citations
3.
Kim, Daehee, et al.. (2021). 1D CNN and Machine Learning Methods for Fall Detection. KIPS Transactions on Software and Data Engineering. 10(3). 85–90. 1 indexed citations
4.
Yoo, Youngjun, et al.. (2020). A Performance Comparison of Super Resolution Model with Different Activation Functions. KIPS Transactions on Software and Data Engineering. 9(10). 303–308. 3 indexed citations
5.
Lee, Jaekoo, Ho Bae, & Sungroh Yoon. (2020). Anomaly Detection by Learning Dynamics From a Graph. IEEE Access. 8. 64356–64365. 4 indexed citations
6.
Lee, Jaekoo, et al.. (2016). Analysis of the German Sport Clubs and Elite Sports Operating System. 14(4). 261–275.
7.
Lee, Jaekoo, et al.. (2016). 체육분야 국가자격증의 실효성 제고방안 연구(II) : 보건의료분야에서 건강운동관리사의 효율적 활용방안. 55(5). 635–644. 1 indexed citations
8.
Lee, Jaekoo, et al.. (2014). Effects of 12week’s Resistance Strength Training on Physiological Variables, Fitness Factors, and Berg Balance Scale in the Long-Term Care Patients(Grade 1). Korean Journal of Sports Science. 23(3). 1279–1289.
9.
Lee, Jaekoo, et al.. (2014). Production of extracellular α-galactosidase by Bacillus sp. LX-1 in solid state fermentation for application as a potential feed additive. Revista Colombiana de Ciencias Pecuarias. 27(3). 194–201. 2 indexed citations
10.
Lee, Jaekoo, et al.. (2013). Optimization of medium composition for α- galactosidase production by Antarctic bacterial isolate, Bacillus sp. LX-1 using response surface methodology. African Journal of Microbiology Research. 7(27). 3494–3500. 4 indexed citations
11.
Lee, Jaekoo, et al.. (2013). Voluntary exercise increases IGF-1, brain-derived neurotrophic factor concentration, and fitness level in child. Korean Journal of Sports Science. 22(1). 889–900.
12.
Lee, Jaekoo, et al.. (2013). Immobilization of the Antarctic <italic>Bacillus</italic> sp. LX-1 α-Galactosidase on Eudragit L-100 for the Production of a Functional Feed Additive. Asian-Australasian Journal of Animal Sciences. 26(4). 552–557. 7 indexed citations
13.
Lee, Jaekoo, et al.. (2012). Bacillus strains as feed additives: In vitro evaluation of its potential probiotic properties. Revista Colombiana de Ciencias Pecuarias. 25(4). 577–585. 27 indexed citations
14.
Lee, Jaekoo, et al.. (2011). The Influences of Jointed Grasswort(Salicornia Herbacea L.) Supplementation and Combined Exercise on Body Composition, Muscle Strength, Bone Mineral Density and Blood Biochemical Parameters in Middle-aged Women of 40 Years. The Korean Journal of Physical Education. 50(1). 211–223. 1 indexed citations
15.
Lee, Wanhee, et al.. (2008). Effects of multifidus muscle volume in patient of lumbar pain according to lumbar exercise methods. Korean Journal of Sports Science. 17(2). 1003–1014. 3 indexed citations
16.
Kim, Minjeong, et al.. (2007). The change of body composition, physical fitness, and capacity of the lungs according to gateball experience in old persons. Korean Journal of Sports Science. 16(1). 417–426. 3 indexed citations
17.
Kim, Sung‐Jin, et al.. (2006). Removal of Aspect-Ratio-Dependent Etching by Low-Angle Forward Reflected Neutral-Beam Etching. 15(4). 387–394. 2 indexed citations
18.
Lee, Jaekoo, et al.. (2005). A Study on the Passive Range of Motion, Specific Pains and Causes of the Pains in Their Shoulders among Hemiplegia Patients. 16(6). 137–148. 1 indexed citations
19.
Yeom, G.Y., et al.. (2004). Removal of Aspect-Ratio-Dependent Etching by Low-Angle Forward Reflected Neutral-Beam Etching. Open Access System for Information Sharing (Pohang University of Science and Technology). 1 indexed citations
20.
Suh, Kyunghyun & Jaekoo Lee. (2003). Investigation of Body-Image Perception, Body Dissatisfaction, and Self-Esteem among Korean Students. The Korean Journal of Growth and Development. 11(2). 77–88.

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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