G. Guy
Impact in
- Computational Mathematics top 10%
-
- Image and Object Detection Techniques
- Medical Image Segmentation Techniques
- Advanced Vision and Imaging
- Advanced Neural Network Applications
- Image Retrieval and Classification Techniques
Papers in
-
- Image and Object Detection Techniques 3
- Visual Attention and Saliency Detection 2
- Advanced Vision and Imaging 2
- Advanced Data Compression Techniques 2
- Advanced Image and Video Retrieval Techniques 1
-
- Video Coding and Compression Technologies 2
- Co-authors
- Gérard G. Medioni (5 shared papers)Its'Hak Dinstein (3 shared papers)Joseph Tzelgov (2 shared papers)Avishai Henik (2 shared papers)Alexandre R. J. François (1 shared paper)H. Rom (1 shared paper)Gad M. Landau (1 shared paper)
- Journals
- International Journal of Computer Vision (1 paper)Pattern Recognition (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Signal Processing (1 paper)Springer eBooks (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
G. Guy
9 papers receiving 472 citations
Peers
Comparison fields: 5 of 43
- Computational Mathematics 14
- Computer Vision and Pattern Recognition 333
- Computer Graphics and Computer-Aided Design 30
- Signal Processing 37
- Cognitive Neuroscience 85
Countries citing papers authored by G. Guy
This map shows the geographic impact of G. Guy'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 G. Guy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Guy more than expected).
Fields of papers citing papers by G. Guy
This network shows the impact of papers produced by G. Guy. 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 G. Guy. The network helps show where G. Guy may publish in the future.
Co-authors
The 7 scholars most cited alongside G. Guy, 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 | 1996 | 250 | |
| 2 | 1997 | 144 | |
| 3 | 2002 | 30 | |
| 4 | 1989 | 22 | |
| 5 | 2003 | 19 | |
| 6 | 1999 | 16 | |
| 7 | 1991 | 12 | |
| 8 | 2003 | 9 | |
| 9 | 2002 | 5 |
About G. Guy
G. Guy is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Cognitive Neuroscience, Computational Mechanics and Media Technology, having authored 9 papers that have together received 507 indexed citations. Recurring topics across this work include Image and Object Detection Techniques (3 papers), Visual Attention and Saliency Detection (2 papers), Advanced Vision and Imaging (2 papers), 3D Shape Modeling and Analysis (2 papers), Visual perception and processing mechanisms (2 papers), Advanced Data Compression Techniques (2 papers), Video Coding and Compression Technologies (2 papers) and Advanced Image and Video Retrieval Techniques (1 paper). The work is most often cited by research in Computational Mathematics (14 citations), Computer Vision and Pattern Recognition (333 citations), Computer Graphics and Computer-Aided Design (30 citations), Signal Processing (37 citations) and Cognitive Neuroscience (85 citations). G. Guy has collaborated with scholars based in United States and Israel. Frequent co-authors include Gérard G. Medioni, Its'Hak Dinstein, Joseph Tzelgov, Avishai Henik, Alexandre R. J. François, H. Rom and Gad M. Landau. Their work appears in journals such as International Journal of Computer Vision, Pattern Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, Signal Processing and Springer eBooks.
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.