Michel Sarkis
- Computer Vision and Pattern Recognition top 5%
- Experimental and Cognitive Psychology top 10%
- Computational Mechanics
- Computer Graphics and Computer-Aided Design top 5%
- Media Technology top 10%
- Topics
- Advanced Vision and Imaging (13 papers)Optical measurement and interference techniques (7 papers)Image Processing Techniques and Applications (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignExperimental and Cognitive Psychology
- Journals
- IEEE Transactions on Image ProcessingIEEE Transactions on Visualization and Computer Graphics2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Michel Sarkis
22 papers receiving 287 citations
Peers
Comparison fields: 5 of 56
- Computer Vision and Pattern Recognition 257
- Experimental and Cognitive Psychology 93
- Computational Mechanics 45
- Computer Graphics and Computer-Aided Design 34
- Media Technology 31
Countries citing papers authored by Michel Sarkis
This map shows the geographic impact of Michel Sarkis'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 Michel Sarkis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michel Sarkis more than expected).
Fields of papers citing papers by Michel Sarkis
This network shows the impact of papers produced by Michel Sarkis. 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 Michel Sarkis. The network helps show where Michel Sarkis may publish in the future.
Co-authorship network of co-authors of Michel Sarkis
This figure shows the co-authorship network connecting the top 25 collaborators of Michel Sarkis. A scholar is included among the top collaborators of Michel Sarkis 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 Michel Sarkis. Michel Sarkis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 18 | |
| 3 | 25 | |
| 4 | 113 | |
| 5 | 19 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 25 | |
| 12 | Towards Real-time Stereo using Non-uniform Image Sampling and Sparse Dynamic Programming | 3 |
| 13 | 1 | |
| 14 | 15 | |
| 15 | 11 | |
| 16 | 0 | |
| 17 | 6 | |
| 18 | 3 | |
| 19 | 1 | |
| 20 | 2 |
About Michel Sarkis
Michel Sarkis is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Media Technology, having authored 26 papers that have together received 300 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (13 papers), Optical measurement and interference techniques (7 papers) and Image Processing Techniques and Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (257 citations), Computer Graphics and Computer-Aided Design (34 citations) and Experimental and Cognitive Psychology (93 citations). Michel Sarkis has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Shang‐Hong Lai, Klaus Diepold, Yiying Tong, Xiaoming Liu, Yawen Lu, Guoyu Lu, Knut Hüper, Ze Zhang, Min Tang and Ravi Ramamoorthi. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Visualization and Computer Graphics and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.