Hazem Raafat
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Signal Processing top 5%
- Information Systems top 10%
- Industrial and Manufacturing Engineering top 10%
- Co-authors
- Qinghan XiaoMohsen RashwanA. S. TolbaG. AudaMohamed S. KamelAhmed RafeaAhmad A. Al SallabMagda B. Fayek
- Topics
- Topic Modeling (7 papers)Industrial Vision Systems and Defect Detection (7 papers)Neural Networks and Applications (6 papers)
In The Last Decade
Hazem Raafat
35 papers receiving 407 citations
Peers
Comparison fields: 5 of 85
- Computer Vision and Pattern Recognition 171
- Artificial Intelligence 164
- Signal Processing 117
- Information Systems 66
- Industrial and Manufacturing Engineering 61
Countries citing papers authored by Hazem Raafat
This map shows the geographic impact of Hazem Raafat'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 Raafat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hazem Raafat more than expected).
Fields of papers citing papers by Hazem Raafat
This network shows the impact of papers produced by Hazem Raafat. 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 Raafat. The network helps show where Hazem Raafat may publish in the future.
Co-authorship network of co-authors of Hazem Raafat
This figure shows the co-authorship network connecting the top 25 collaborators of Hazem Raafat. A scholar is included among the top collaborators of Hazem Raafat 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 Raafat. Hazem Raafat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 40 | |
| 3 | Vector Based Techniques for Short Answer Grading. | 21 |
| 4 | RDI System for Extrinsic Plagiarism Detection (RDI_RED), Working Notes for PANAraPlagDet at FIRE 2015. | 7 |
| 5 | Cross Lingual Lexical Substitution Using Word Representation in Vector Space. | 0 |
| 6 | 37 | |
| 7 | 2 | |
| 8 | 22 | |
| 9 | 5 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 0 | |
| 13 | 6 | |
| 14 | 7 | |
| 15 | 2 | |
| 16 | 4 | |
| 17 | 24 | |
| 18 | 12 | |
| 19 | 6 | |
| 20 | 12 |
About Hazem Raafat
Hazem Raafat is a scholar working on Signal Processing, Industrial and Manufacturing Engineering and Computer Vision and Pattern Recognition, having authored 38 papers that have together received 451 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Industrial Vision Systems and Defect Detection (7 papers) and Neural Networks and Applications (6 papers). The work is most often cited by research in Signal Processing (117 citations), Computer Vision and Pattern Recognition (171 citations) and Industrial and Manufacturing Engineering (61 citations). Hazem Raafat has collaborated with scholars based in Canada, Kuwait and Egypt. Frequent co-authors include Qinghan Xiao, Mohsen Rashwan, A. S. Tolba, G. Auda, Mohamed S. Kamel, Ahmed Rafea, Ahmad A. Al Sallab, Magda B. Fayek, D. C. D. Oguamanam and Andrew K. C. Wong. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and Pattern Recognition.
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.