David J. Yoon

462 citations
13 papers · 304 indexed · h-index 10
Topics
Robotics and Sensor-Based Localization (7 papers)Autonomous Vehicle Technology and Safety (6 papers)Anomaly Detection Techniques and Applications (4 papers)
Partner nations
CanadaChinaUnited States

In The Last Decade

David J. Yoon

12 papers receiving 296 citations

Peers

David J. Yoon
Comparison fields: 5 of 36
  • Aerospace Engineering 208
  • Computer Vision and Pattern Recognition 102
  • Electrical and Electronic Engineering 69
  • Artificial Intelligence 63
  • Environmental Engineering 51
Replace Paul Murcutt with:
Paul Murcutt United Kingdom
Ziyang Hong China
Josip Ćesić Croatia
Yingying Ran China
Martin Holder Germany
Zebang Yang China
Ben Caine United States
Aljoša Ošep Germany
Mingxing Wen Singapore
Ian Baldwin United Kingdom
David J. Yoon relative to Paul Murcutt United Kingdom Paul Murcutt's profile →
Citations per field
00.5×1.5×
Paul Murcutt · 1×
Citations per year

Countries citing papers authored by David J. Yoon

Since Specialization
Citations

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

Fields of papers citing papers by David J. Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Yoon. 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 David J. Yoon. The network helps show where David J. Yoon may publish in the future.

Co-authorship network of co-authors of David J. Yoon

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1 0
2 5
3 11
4 1
5 81
6 50
7 20
8 10
9 49
10 19
11 18
12 27
13 13

About David J. Yoon

David J. Yoon is a scholar working on Instrumentation, Automotive Engineering and Aerospace Engineering, having authored 13 papers that have together received 304 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (7 papers), Autonomous Vehicle Technology and Safety (6 papers) and Anomaly Detection Techniques and Applications (4 papers). The work is most often cited by research in Instrumentation (41 citations), Aerospace Engineering (208 citations) and Geology (30 citations). David J. Yoon has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Timothy D. Barfoot, Angela P. Schoellig, Tim Barfoot, Shichen Lu, Andrew Lambert, Haowei Zhang, Soeren Kammel, Patrick McGarey, François Pomerleau and Haowei Zhang. Their work appears in journals such as The International Journal of Robotics Research, IEEE Robotics and Automation Letters and Journal of Field Robotics.

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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