J. Edward Swan

107 papers receiving 3.0k citations

Hit Papers

Perceptual issues in augmented reality revisited201020262015202020102018100200300

Peers

J. Edward Swan
Comparison fields: 5 of 134
  • Computer Vision and Pattern Recognition 2.1k
  • Human-Computer Interaction 2.0k
  • Cognitive Neuroscience 656
  • Media Technology 503
  • Automotive Engineering 364
Replace Carolina Cruz‐Neira with:
Carolina Cruz‐Neira United States
Gudrun Klinker Germany
Ernst Kruijff Germany
Daniel J. Sandin United States
Thomas A. DeFanti United States
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Eyal Ofek United States
Victoria Interrante United States
Mark Bolas United States
Stephen R. Ellis United States
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Citations per field
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Citations per year

Countries citing papers authored by J. Edward Swan

Since Specialization
Citations

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

Fields of papers citing papers by J. Edward Swan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Edward Swan

This figure shows the co-authorship network connecting the top 25 collaborators of J. Edward Swan. A scholar is included among the top collaborators of J. Edward Swan 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 J. Edward Swan. J. Edward Swan 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
#WorkIndexed citations
1 0
2 11
3 92
4 72
5 30
6
Improved SPAAM Robustness through Stereo Calibration.
3
7 24
8 12
9 1
10 19
11
Perceptual and Ergonomic Issues in Mobile Augmented Reality for Urban Operations
5
12 86
13
Proceedings of the conference on Visualization '02
146
14 3
15 7
16 13
17 1
18 27
19 14
20 6

About J. Edward Swan

J. Edward Swan is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 116 papers that have together received 3.2k indexed citations. Recurring topics across this work include Augmented Reality Applications (55 papers), Virtual Reality Applications and Impacts (43 papers) and Interactive and Immersive Displays (24 papers). The work is most often cited by research in Human-Computer Interaction (2.0k citations), Computer Vision and Pattern Recognition (2.1k citations) and Computer Graphics and Computer-Aided Design (261 citations). J. Edward Swan has collaborated with scholars based in United States, Japan and New Zealand. Frequent co-authors include Joseph L. Gabbard, Deborah Hix, Gurjot Singh, Steven Feiner, Ernst Kruijff, Stephen R. Ellis, J. Adam Jones, Mark Livingston, Mark Billinghurst and Arindam Dey. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Journal of Vision and Computer Graphics Forum.

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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