Juseong Lee

14 papers receiving 317 citations

Hit Papers

Deep reinforcement learning for predictive aircraft maint...202220262023202420224080120

Peers

Juseong Lee
Comparison fields: 5 of 74
  • Safety, Risk, Reliability and Quality 124
  • Control and Systems Engineering 113
  • Computer Vision and Pattern Recognition 68
  • Statistics, Probability and Uncertainty 56
  • Industrial and Manufacturing Engineering 42
Replace Hui Shi with:
Hui Shi China
Leonardo Ramos Rodrigues Brazil
Guixiang Shen China
Ivo Paixão de Medeiros Brazil
Binbin Xu China
Hong-Zhong Huang China
Hongsheng Su China
Jinfei Shi China
Himanshu Upadhyay United States
Juseong Lee relative to Hui Shi China Hui Shi's profile →
Citations per field
00.5×2.5×
Hui Shi · 1×
Citations per year

Countries citing papers authored by Juseong Lee

Since Specialization
Citations

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

Fields of papers citing papers by Juseong Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juseong Lee

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 10
2 0
3 7
4
Deep reinforcement learning for predictive aircraft maintenance using probabilistic Remaining-Useful-Life prognosticsbreakdown →
123
5 0
6 32
7 4
8 67
9 4
10 11
11 1
12 2
13 0
14 1
15 1
16 68
17 4

About Juseong Lee

Juseong Lee is a scholar working on Software, Safety, Risk, Reliability and Quality and Media Technology, having authored 17 papers that have together received 335 indexed citations. Recurring topics across this work include Software Reliability and Analysis Research (6 papers), Reliability and Maintenance Optimization (6 papers) and Image Processing Techniques and Applications (5 papers). The work is most often cited by research in Medical Laboratory Technology (27 citations), Safety, Risk, Reliability and Quality (124 citations) and Statistics, Probability and Uncertainty (56 citations). Juseong Lee has collaborated with scholars based in Netherlands, South Korea and France. Frequent co-authors include Mihaela Mitici, Hoyoung Tang, Jongsun Park, Yonghyun Kim, Pierre Bieber, Bum-Jae You, Dong Joo Seo, Kshitiz Gupta, H.A.P. Blom and Eun Hyun Ahn. Their work appears in journals such as Reliability Engineering & System Safety, IEEE Transactions on Circuits and Systems for Video Technology and Anticancer Research.

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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