Amr Suleiman
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Aerospace Engineering top 10%
- Artificial Intelligence
- Mechanical Engineering
- Co-authors
- Vivienne SzeZhengdong ZhangLuca CarloneSertaç KaramanJoel EmerYu‐Hsin ChenS. E. D. HabibVladimir Stojanović
- Topics
- Advanced Image and Video Retrieval Techniques (6 papers)CCD and CMOS Imaging Sensors (6 papers)Advanced Neural Network Applications (5 papers)
- Journals
- IEEE Journal of Solid-State CircuitsIEEE Transactions on Circuits and Systems I Regular PapersJournal of Signal Processing Systems
- Partner nations
- United StatesEgypt
In The Last Decade
Amr Suleiman
12 papers receiving 318 citations
Peers
Comparison fields: 5 of 57
- Computer Vision and Pattern Recognition 197
- Electrical and Electronic Engineering 146
- Aerospace Engineering 101
- Artificial Intelligence 42
- Mechanical Engineering 31
Countries citing papers authored by Amr Suleiman
This map shows the geographic impact of Amr Suleiman'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 Amr Suleiman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amr Suleiman more than expected).
Fields of papers citing papers by Amr Suleiman
This network shows the impact of papers produced by Amr Suleiman. 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 Amr Suleiman. The network helps show where Amr Suleiman may publish in the future.
Co-authorship network of co-authors of Amr Suleiman
This figure shows the co-authorship network connecting the top 25 collaborators of Amr Suleiman. A scholar is included among the top collaborators of Amr Suleiman 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 Amr Suleiman. Amr Suleiman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 99 | |
| 2 | 31 | |
| 3 | 68 | |
| 4 | 25 | |
| 5 | 12 | |
| 6 | 3 | |
| 7 | 12 | |
| 8 | 44 | |
| 9 | 22 | |
| 10 | 4 | |
| 11 | 3 | |
| 12 | 4 |
About Amr Suleiman
Amr Suleiman is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Computer Networks and Communications, having authored 12 papers that have together received 327 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (6 papers), CCD and CMOS Imaging Sensors (6 papers) and Advanced Neural Network Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (197 citations), Hardware and Architecture (28 citations) and Aerospace Engineering (101 citations). Amr Suleiman has collaborated with scholars based in United States and Egypt. Frequent co-authors include Vivienne Sze, Zhengdong Zhang, Luca Carlone, Sertaç Karaman, Joel Emer, Yu‐Hsin Chen, S. E. D. Habib, Vladimir Stojanović, Mohamed I. Ali and Shoukry I. Shams. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Circuits and Systems I Regular Papers and Journal of Signal Processing Systems.
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.