El-Sayed M. El-Horbaty
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Neurology top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Abdel-Badeeh M. SalemEl‐Sayed A. El‐DahshanHeba MohsenMarco AlfonseBassant M. ElbagouryMohamed KhalifaHala H. ZayedAhmed Taha
- Topics
- Anomaly Detection Techniques and Applications (5 papers)Chaos-based Image/Signal Encryption (5 papers)Human Pose and Action Recognition (5 papers)
In The Last Decade
El-Sayed M. El-Horbaty
48 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 541
- Computer Vision and Pattern Recognition 521
- Neurology 516
- Radiology, Nuclear Medicine and Imaging 214
- Computer Networks and Communications 110
Countries citing papers authored by El-Sayed M. El-Horbaty
This map shows the geographic impact of El-Sayed M. El-Horbaty'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 El-Sayed M. El-Horbaty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites El-Sayed M. El-Horbaty more than expected).
Fields of papers citing papers by El-Sayed M. El-Horbaty
This network shows the impact of papers produced by El-Sayed M. El-Horbaty. 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 El-Sayed M. El-Horbaty. The network helps show where El-Sayed M. El-Horbaty may publish in the future.
Co-authorship network of co-authors of El-Sayed M. El-Horbaty
This figure shows the co-authorship network connecting the top 25 collaborators of El-Sayed M. El-Horbaty. A scholar is included among the top collaborators of El-Sayed M. El-Horbaty 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 El-Sayed M. El-Horbaty. El-Sayed M. El-Horbaty is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | 12 | |
| 10 | A Study on Cloud Computing Architectures for Smart Healthcare Services. | 1 |
| 11 | 0 | |
| 12 | 41 | |
| 13 | 19 | |
| 14 | 4 | |
| 15 | 15 | |
| 16 | 13 | |
| 17 | 4 | |
| 18 | An improved parallel minimum spanning tree based clustering algorithm for microarrays data analysis | 2 |
| 19 | Autoregressive Filter Algorithm for Sifting Digital Images. | 1 |
| 20 | 1 |
About El-Sayed M. El-Horbaty
El-Sayed M. El-Horbaty is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 54 papers that have together received 1.1k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (5 papers), Chaos-based Image/Signal Encryption (5 papers) and Human Pose and Action Recognition (5 papers). The work is most often cited by research in Neurology (516 citations), Computer Vision and Pattern Recognition (521 citations) and Artificial Intelligence (541 citations). El-Sayed M. El-Horbaty has collaborated with scholars based in Egypt, Iraq and France. Frequent co-authors include Abdel-Badeeh M. Salem, El‐Sayed A. El‐Dahshan, Heba Mohsen, Marco Alfonse, Bassant M. Elbagoury, Mohamed Khalifa, Hala H. Zayed, Ahmed Taha, Safia Abbas and Abdel-Badeeh M. Salem. Their work appears in journals such as Applied Mathematics and Computation, Applied Sciences and Neural Computing and Applications.
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.