Hazem M. Abbas
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Signal Processing top 5%
- Media Technology top 5%
- Co-authors
- Mahmoud I. KhalilM.M. FahmyM.M. BayoumiA.A. Abdul AzimAhmed AllamHossam S. HassaneinMohamed MoustafaM. Watheq El‐Kharashi
- Topics
- Neural Networks and Applications (21 papers)VLSI and FPGA Design Techniques (8 papers)Handwritten Text Recognition Techniques (8 papers)
In The Last Decade
Hazem M. Abbas
106 papers receiving 969 citations
Peers
Comparison fields: 5 of 114
- Computer Vision and Pattern Recognition 393
- Artificial Intelligence 286
- Electrical and Electronic Engineering 162
- Signal Processing 128
- Media Technology 124
Countries citing papers authored by Hazem M. Abbas
This map shows the geographic impact of Hazem M. Abbas'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 Hazem M. Abbas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hazem M. Abbas more than expected).
Fields of papers citing papers by Hazem M. Abbas
This network shows the impact of papers produced by Hazem M. Abbas. 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 Hazem M. Abbas. The network helps show where Hazem M. Abbas may publish in the future.
Co-authorship network of co-authors of Hazem M. Abbas
This figure shows the co-authorship network connecting the top 25 collaborators of Hazem M. Abbas. A scholar is included among the top collaborators of Hazem M. Abbas 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 Hazem M. Abbas. Hazem M. Abbas 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 | 3 | |
| 3 | 6 | |
| 4 | 23 | |
| 5 | 4 | |
| 6 | 2 | |
| 7 | 20 | |
| 8 | 17 | |
| 9 | 7 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | 1 | |
| 13 | Neural generalized predictive controller stability analysis | 1 |
| 14 | Neural Generalized Predictive Controller and internal model principle | 1 |
| 15 | 12 | |
| 16 | 4 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 6 | |
| 20 | 26 |
About Hazem M. Abbas
Hazem M. Abbas is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture and Artificial Intelligence, having authored 109 papers that have together received 1.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (21 papers), VLSI and FPGA Design Techniques (8 papers) and Handwritten Text Recognition Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (393 citations), Metals and Alloys (39 citations) and Media Technology (124 citations). Hazem M. Abbas has collaborated with scholars based in Egypt, Canada and Hungary. Frequent co-authors include Mahmoud I. Khalil, M.M. Fahmy, M.M. Bayoumi, A.A. Abdul Azim, Ahmed Allam, Hossam S. Hassanein, Mohamed Moustafa, M. Watheq El‐Kharashi, Aboelmagd Noureldin and Hatem Abou-Zeid. Their work appears in journals such as Journal of Power Sources, IEEE Access and Corrosion Science.
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.