Carl Case
Impact in
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- Handwritten Text Recognition Techniques
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Image Processing and 3D Reconstruction
- Image and Object Detection Techniques
- Video Analysis and Summarization
- Media Technology top 5%
- Vehicle License Plate Recognition
Papers in
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- Advanced Image and Video Retrieval Techniques 2
- Image and Signal Denoising Methods 1
- Data Visualization and Analytics 1
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- Neural Networks and Applications 2
- Co-authors
- Andrew Y. Ng (2 shared papers)Adam Coates (2 shared papers)Tao Wang (1 shared paper)Sanjeev Satheesh (1 shared paper)David J. Wu (1 shared paper)Vitaly Lavrukhin (1 shared paper)Igor Gitman (1 shared paper)Paulius Micikevicius (1 shared paper)
- Journals
- arXiv (Cornell University) (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (5 papers)
- Partner nations
- United StatesAustralia
In The Last Decade
Carl Case
7 papers receiving 303 citations
Peers
Comparison fields: 5 of 60
- Computer Vision and Pattern Recognition 272
- Media Technology 105
- Human-Computer Interaction 12
- Artificial Intelligence 57
- Computational Mathematics 1
Countries citing papers authored by Carl Case
This map shows the geographic impact of Carl Case'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 Carl Case with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carl Case more than expected).
Fields of papers citing papers by Carl Case
This network shows the impact of papers produced by Carl Case. 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 Carl Case. The network helps show where Carl Case may publish in the future.
Co-authors
The 13 scholars most cited alongside Carl Case, 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 | 2011 | 278 | |
| 2 | 2011 | 30 | |
| 3 | 2002 | 9 | |
| 4 | 2018 | 8 | |
| 5 | 2002 | 4 | |
| 6 | 2003 | 3 | |
| 7 | 2002 | 2 | |
| 8 | 2002 | 1 |
About Carl Case
Carl Case is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Astronomy and Astrophysics, Statistical and Nonlinear Physics and Atomic and Molecular Physics, and Optics, having authored 8 papers that have together received 335 indexed citations. Recurring topics across this work include Neural Networks and Applications (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Robotics and Sensor-Based Localization (1 paper), Stock Market Forecasting Methods (1 paper), Astronomical Observations and Instrumentation (1 paper), Adaptive optics and wavefront sensing (1 paper), Image and Signal Denoising Methods (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (272 citations), Media Technology (105 citations), Human-Computer Interaction (12 citations), Artificial Intelligence (57 citations) and Computational Mathematics (1 citation). Carl Case has collaborated with scholars based in United States and Australia. Frequent co-authors include Andrew Y. Ng, Adam Coates, Tao Wang, Sanjeev Satheesh, David J. Wu, Vitaly Lavrukhin, Igor Gitman, Paulius Micikevicius, Boris Ginsburg and Oleksii Kuchaiev. Their work appears in journals such as arXiv (Cornell University) and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.