Gyu-In Jee

1.4k citations
85 papers · 1.1k · h-index 22

Impact in

Papers in

Gyu-In Jee

77 papers receiving 1.0k citations

Peers

Gyu-In Jee
Comparison fields: 5 of 72
  • Aerospace Engineering 635
  • Electrical and Electronic Engineering 494
  • Ocean Engineering 128
  • Artificial Intelligence 248
  • Automotive Engineering 82
Replace David Bétaille with:
David Bétaille France
Xingqun Zhan China
Lawrence R. Weill United States
Jacques Georgy Canada
Juliette Marais France
Gert F. Trommer Germany
Marion Berbineau France
Emmanuel Duflos France
Mohamed Atia Canada
Axel Barrau France
Gyu-In Jee relative to David Bétaille France David Bétaille's profile →
Citations per field
00.5×1.7×
David Bétaille · 1×
Citations per year

Countries citing papers authored by Gyu-In Jee

Since Specialization
Citations

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

Fields of papers citing papers by Gyu-In Jee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gyu-In Jee. 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 Gyu-In Jee. The network helps show where Gyu-In Jee may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199575
2 200665
3 201560
4 200258
5 201554
6 200952
7 201647
8 199641
9 200340
10 200331
11
Carrier Tracking Loop using the Adaptive Two-Stage Kalman Filter for High Dynamic Situations
200830
12 198128
13 201827
14 202225
15 201225
16 200523
17 200223
18 201123
19
GPS Signal Degradation Modeling
200122
20 200822

About Gyu-In Jee

Gyu-In Jee is a scholar working on Aerospace Engineering, Electrical and Electronic Engineering, Artificial Intelligence, Automotive Engineering and Computer Networks and Communications, having authored 85 papers that have together received 1.1k indexed citations. Recurring topics across this work include GNSS positioning and interference (47 papers), Inertial Sensor and Navigation (31 papers), Target Tracking and Data Fusion in Sensor Networks (28 papers), Indoor and Outdoor Localization Technologies (25 papers), Robotics and Sensor-Based Localization (15 papers), Autonomous Vehicle Technology and Safety (9 papers), Advanced Frequency and Time Standards (7 papers) and Remote Sensing and LiDAR Applications (6 papers). The work is most often cited by research in Aerospace Engineering (635 citations), Electrical and Electronic Engineering (494 citations), Ocean Engineering (128 citations), Artificial Intelligence (248 citations) and Automotive Engineering (82 citations). Gyu-In Jee has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Kwang-Hoon Kim, Byung-Hyun Lee, Jang Gyu Lee, L. N. Hannett, B. Fardanesh, J.G. Lee, Wook Kim, Jang Gyu Lee, Kyuwon Kim and Hyoung Joong Kim. Their work appears in journals such as Sensors, GPS Solutions, Journal of Guidance Control and Dynamics, IEEE Transactions on Intelligent Transportation Systems and IEEE Access.

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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