Dae Hee Won

556 citations
35 papers · 433 indexed · h-index 12

Impact in

Papers in

Dae Hee Won

32 papers receiving 406 citations

Peers

Dae Hee Won
Comparison fields: 5 of 61
  • Aerospace Engineering 296
  • Environmental Engineering 64
  • Geology 18
  • Computer Vision and Pattern Recognition 64
  • Oceanography 37
Replace Ole Schumann with:
Ole Schumann Germany
Hoi‐Fung Ng Hong Kong
Yi Dong China
D.R. Blidberg United States
Hanshan Li China
Xin Lai China
Ni Zhu France
Guang-Je Tsai Taiwan
Aitor Saenz‐Aguirre Spain
Dae Hee Won relative to Ole Schumann Germany Ole Schumann's profile →
Citations per field
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Citations per year

Countries citing papers authored by Dae Hee Won

Since Specialization
Citations

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

Fields of papers citing papers by Dae Hee Won

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae Hee Won. 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 Dae Hee Won. The network helps show where Dae Hee Won may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201447
2 201244
3 201342
4 200542
5 201431
6 201027
7 201426
8 201525
9 201619
10 201518
11 200813
12 201613
13
Particle Filtering Approach To Fault Detection and Isolation for GPS Integrity Monitoring
20069
14 20119
15 20159
16 20188
17 20127
18
Development of A Wearable Input Device Recognizing Human Hand and Finger Motions as A New Mobile Input Device
20016
19 20095
20 20115

About Dae Hee Won

Dae Hee Won is a scholar working on Aerospace Engineering, Artificial Intelligence, Electrical and Electronic Engineering, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 35 papers that have together received 433 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (13 papers), Inertial Sensor and Navigation (12 papers), GNSS positioning and interference (12 papers), Target Tracking and Data Fusion in Sensor Networks (7 papers), Indoor and Outdoor Localization Technologies (6 papers), Robotic Path Planning Algorithms (4 papers), Fault Detection and Control Systems (3 papers) and Soil Moisture and Remote Sensing (3 papers). The work is most often cited by research in Aerospace Engineering (296 citations), Environmental Engineering (64 citations), Geology (18 citations), Computer Vision and Pattern Recognition (64 citations) and Oceanography (37 citations). Dae Hee Won has collaborated with scholars based in South Korea, United States and Vietnam. Frequent co-authors include Sangkyung Sung, Young Jae Lee, Moon-Beom Heo, Dennis Akos, Jiyun Lee, Eunsung Lee, Seung‐Woo Lee, Min-Sung Kang, SangJoo Kwon and Junpyo Park. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, GPS Solutions, Applied Surface Science, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and Materials.

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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