Rami Al‐Hmouz
- Artificial Intelligence top 2%
- Management Science and Operations Research top 1%
- Computational Theory and Mathematics top 1%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Co-authors
- Ali MorfeqAbdullah BalamashWitold PedryczEnrique Herrera‐ViedmaFrancisco Javier CabrerizoJun ShenJun YanSubhash Challa
- Topics
- Rough Sets and Fuzzy Logic (23 papers)Fuzzy Logic and Control Systems (12 papers)Handwritten Text Recognition Techniques (10 papers)
- Cited by
- Management Science and Operations ResearchComputational Theory and MathematicsArtificial Intelligence
- Partner nations
- Saudi ArabiaCanadaPoland
In The Last Decade
Rami Al‐Hmouz
64 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 583
- Management Science and Operations Research 475
- Computational Theory and Mathematics 366
- Computer Vision and Pattern Recognition 194
- Information Systems 147
Countries citing papers authored by Rami Al‐Hmouz
This map shows the geographic impact of Rami Al‐Hmouz'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 Rami Al‐Hmouz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rami Al‐Hmouz more than expected).
Fields of papers citing papers by Rami Al‐Hmouz
This network shows the impact of papers produced by Rami Al‐Hmouz. 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 Rami Al‐Hmouz. The network helps show where Rami Al‐Hmouz may publish in the future.
Co-authorship network of co-authors of Rami Al‐Hmouz
This figure shows the co-authorship network connecting the top 25 collaborators of Rami Al‐Hmouz. A scholar is included among the top collaborators of Rami Al‐Hmouz 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 Rami Al‐Hmouz. Rami Al‐Hmouz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 12 | |
| 7 | Deep Learning Autoencoder Approach: Automatic Recognition of Artistic Arabic Calligraphy Types | 10 |
| 8 | 19 | |
| 9 | 7 | |
| 10 | 4 | |
| 11 | 20 | |
| 12 | Fuzzy c means based hybrid classifiers for offline recognition of handwritten indian (Arabic) numerals | 7 |
| 13 | 50 | |
| 14 | 3 | |
| 15 | 53 | |
| 16 | 6 | |
| 17 | 16 | |
| 18 | 5 | |
| 19 | 29 | |
| 20 | 21 |
About Rami Al‐Hmouz
Rami Al‐Hmouz is a scholar working on Computational Theory and Mathematics, Signal Processing and Artificial Intelligence, having authored 70 papers that have together received 1.3k indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (23 papers), Fuzzy Logic and Control Systems (12 papers) and Handwritten Text Recognition Techniques (10 papers). The work is most often cited by research in Management Science and Operations Research (475 citations), Computational Theory and Mathematics (366 citations) and Artificial Intelligence (583 citations). Rami Al‐Hmouz has collaborated with scholars based in Saudi Arabia, Canada and Poland. Frequent co-authors include Ali Morfeq, Abdullah Balamash, Witold Pedrycz, Enrique Herrera‐Viedma, Francisco Javier Cabrerizo, Jun Shen, Jun Yan, Subhash Challa, Francisco Chiclana and Mohammad Momani. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and IEEE Access.
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.