Diego Nehab
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- Computer Graphics and Visualization Techniques 35
- Space and Planetary Science top 1%
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- Advanced Vision and Imaging 30
- Advanced Image and Video Retrieval Techniques 12
- Advanced Image Processing Techniques 11
- Image and Signal Denoising Methods 7
- Medical Image Segmentation Techniques 3
- Geology top 2%
- Computational Mechanics top 2%
- 3D Shape Modeling and Analysis 10
- Sparse and Compressive Sensing Techniques 4
- Co-authors
- Szymon RusinkiewiczJames DavisRavi RamamoorthiPedro V. SanderHugues HoppeJason LawrenceLei YangTim Weyrich
- Cited by
- Computer Graphics and Computer-Aided DesignSpace and Planetary ScienceComputer Vision and Pattern Recognition
- Journals
- IEEE Transactions on Image Processing (1 paper)ACM Transactions on Graphics (15 papers)Health & Place (1 paper)
- Partner nations
- United StatesBrazilUnited Kingdom
In The Last Decade
Diego Nehab
52 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 68
- Computer Graphics and Computer-Aided Design 688
- Space and Planetary Science 67
- Computer Vision and Pattern Recognition 1.0k
- Geology 207
- Computational Mechanics 381
Countries citing papers authored by Diego Nehab
This map shows the geographic impact of Diego Nehab'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 Diego Nehab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Nehab more than expected).
Fields of papers citing papers by Diego Nehab
This network shows the impact of papers produced by Diego Nehab. 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 Diego Nehab. The network helps show where Diego Nehab may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Diego Nehab, 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 | 2018 | 1 | |
| 2 | 2016 | 9 | |
| 3 | 2015 | 7 | |
| 4 | 2014 | 7 | |
| 5 | Advances in 3D Shape Acquisition | 2014 | 1 |
| 6 | 2014 | 11 | |
| 7 | 2014 | 7 | |
| 8 | 2012 | 34 | |
| 9 | 2011 | 1 | |
| 10 | 2011 | 4 | |
| 11 | 2011 | 27 | |
| 12 | 2011 | 37 | |
| 13 | 2010 | 3 | |
| 14 | 2010 | 17 | |
| 15 | 2008 | 5 | |
| 16 | 2008 | 38 | |
| 17 | 2007 | 75 | |
| 18 | 2007 | 5 | |
| 19 | 2007 | 37 | |
| 20 | 2006 | 10 |
About Diego Nehab
Diego Nehab is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 53 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (35 papers), Advanced Vision and Imaging (30 papers), Advanced Image and Video Retrieval Techniques (12 papers), Advanced Image Processing Techniques (11 papers), 3D Shape Modeling and Analysis (10 papers), Image and Signal Denoising Methods (7 papers), Sparse and Compressive Sensing Techniques (4 papers) and Medical Image Segmentation Techniques (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (688 citations), Space and Planetary Science (67 citations) and Computer Vision and Pattern Recognition (1.0k citations). Diego Nehab has collaborated with scholars based in United States, Brazil and United Kingdom. Frequent co-authors include Szymon Rusinkiewicz, James Davis, Ravi Ramamoorthi, Pedro V. Sander, Hugues Hoppe, Jason Lawrence, Lei Yang, Tim Weyrich, Philip Shilane and John Isidoro. Their work appears in journals such as IEEE Transactions on Image Processing, ACM Transactions on Graphics and Health & Place.
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.