Eric Penner
Impact in
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- Computer Graphics and Visualization Techniques
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- Advanced Vision and Imaging
- Advanced Image Processing Techniques
- Image Enhancement Techniques
- Generative Adversarial Networks and Image Synthesis
Papers in
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- Advanced Vision and Imaging 6
- Advanced Image Processing Techniques 3
- Image Enhancement Techniques 2
- Augmented Reality Applications 1
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- Computer Graphics and Visualization Techniques 5
- Co-authors
- Li Zhang (1 shared paper)Ross G. Mitchell (1 shared paper)Douglas Lanman (6 shared papers)George Borshukov (2 shared papers)J.R. Parker (1 shared paper)Grace Kuo (2 shared papers)Nathan Matsuda (3 shared papers)Yang Zhao (1 shared paper)
- Journals
- ACM Transactions on Graphics (1 paper)Eurographics (1 paper)
- Partner nations
- United StatesCanadaSwitzerland
In The Last Decade
Eric Penner
13 papers receiving 284 citations
Peers
Comparison fields: 5 of 34
- Computer Graphics and Computer-Aided Design 165
- Computer Vision and Pattern Recognition 253
- Media Technology 34
- Human-Computer Interaction 19
- Computational Mechanics 59
Countries citing papers authored by Eric Penner
This map shows the geographic impact of Eric Penner'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 Eric Penner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Penner more than expected).
Fields of papers citing papers by Eric Penner
This network shows the impact of papers produced by Eric Penner. 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 Eric Penner. The network helps show where Eric Penner may publish in the future.
Co-authors
The 21 scholars most cited alongside Eric Penner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 239 | |
| 2 | 2008 | 15 | |
| 3 | 2023 | 7 | |
| 4 | 2023 | 7 | |
| 5 | 2023 | 6 | |
| 6 | 2023 | 4 | |
| 7 | 2018 | 4 | |
| 8 | 2007 | 3 | |
| 9 | 2023 | 2 | |
| 10 | 2023 | 2 | |
| 11 | 2014 | 2 | |
| 12 | 2012 | 1 | |
| 13 | 2011 | 1 | |
| 14 | 2024 | 0 | |
| 15 | A GPU Cluster Without the Clutter: A Drop-in Scalable Programmable-Pipeline with Several GPUs and Only One PC | 2006 | 0 |
About Eric Penner
Eric Penner is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Media Technology, Computational Mechanics and Cognitive Neuroscience, having authored 15 papers that have together received 293 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (6 papers), Computer Graphics and Visualization Techniques (5 papers), Advanced Optical Imaging Technologies (4 papers), 3D Shape Modeling and Analysis (3 papers), Advanced Image Processing Techniques (3 papers), Image Enhancement Techniques (2 papers), Virtual Reality Applications and Impacts (2 papers) and Augmented Reality Applications (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (165 citations), Computer Vision and Pattern Recognition (253 citations), Media Technology (34 citations), Human-Computer Interaction (19 citations) and Computational Mechanics (59 citations). Eric Penner has collaborated with scholars based in United States, Canada and Switzerland. Frequent co-authors include Li Zhang, Ross G. Mitchell, Douglas Lanman, George Borshukov, J.R. Parker, Grace Kuo, Nathan Matsuda, Yang Zhao, Olivier Mercier and Timothy N. Lambert. Their work appears in journals such as ACM Transactions on Graphics and Eurographics.
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.