Mohamed Gabr
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- Chaos-based Image/Signal Encryption 28
- Advanced Steganography and Watermarking Techniques 12
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- Cellular Automata and Applications 15
- Mathematical Physics top 10%
- Artificial Intelligence top 10%
- Coding theory and cryptography 9
- Cryptographic Implementations and Security 6
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- DNA and Biological Computing 2
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- Cardiac Arrhythmias and Treatments 2
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- Wireless Communication Security Techniques 2
Mohamed Gabr
31 papers receiving 642 citations
Hit Papers
Peers
Comparison fields: 5 of 37
- Computer Vision and Pattern Recognition 606
- Computational Theory and Mathematics 210
- Mathematical Physics 80
- Statistical and Nonlinear Physics 80
- Artificial Intelligence 192
Countries citing papers authored by Mohamed Gabr
This map shows the geographic impact of Mohamed Gabr'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 Mohamed Gabr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Gabr more than expected).
Fields of papers citing papers by Mohamed Gabr
This network shows the impact of papers produced by Mohamed Gabr. 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 Mohamed Gabr. The network helps show where Mohamed Gabr may publish in the future.
Co-authorship network
The 24 scholars most cited alongside Mohamed Gabr, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 43 | |
| 5 | Image Encryption Based on Fourier-DNA Coding for Hyperchaotic Chen System, Chen-Based Binary Quantization S-Box, and Variable-Base Modulo Operationbreakdown → | 2024 | 60 |
| 6 | 2024 | 13 | |
| 7 | 2024 | 29 | |
| 8 | 2024 | 21 | |
| 9 | 2024 | 32 | |
| 10 | 2024 | 0 | |
| 11 | 2024 | 14 | |
| 12 | 2023 | 0 | |
| 13 | 2023 | 49 | |
| 14 | 2023 | 45 | |
| 15 | 2023 | 2 | |
| 16 | 2023 | 82 | |
| 17 | 2023 | 2 | |
| 18 | 2023 | 1 | |
| 19 | 2023 | 1 | |
| 20 | 2022 | 1 |
About Mohamed Gabr
Mohamed Gabr is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Artificial Intelligence, having authored 35 papers that have together received 658 indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (28 papers), Cellular Automata and Applications (15 papers), Advanced Steganography and Watermarking Techniques (12 papers), Coding theory and cryptography (9 papers), Cryptographic Implementations and Security (6 papers), DNA and Biological Computing (2 papers), Cardiac Arrhythmias and Treatments (2 papers) and Wireless Communication Security Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (606 citations), Computational Theory and Mathematics (210 citations) and Mathematical Physics (80 citations). Mohamed Gabr has collaborated with scholars based in Egypt, Malaysia and United States. Frequent co-authors include Wassim Alexan, Dina El-Damak, Rimon Elias, Lip Yee Por, Yen‐Lin Chen, Amr Aboshousha, Khalid M. Hosny, George A. Papakostas, Chin Soon Ku and Eman Azab. Their work appears in journals such as IEEE Access, JACC. Clinical electrophysiology, Symmetry, Fractal and Fractional and IET Image Processing.
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.