Maher I. Rajab
- Oncology
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Civil and Structural Engineering
- Biomedical Engineering
- Topics
- Cutaneous Melanoma Detection and Management (7 papers)Asphalt Pavement Performance Evaluation (5 papers)Infrastructure Maintenance and Monitoring (5 papers)
- Journals
- Computerized Medical Imaging and GraphicsSkin Research and TechnologyRoad Materials and Pavement Design
- Partner nations
- Saudi ArabiaUnited KingdomJapan
In The Last Decade
Maher I. Rajab
17 papers receiving 278 citations
Peers
Comparison fields: 5 of 57
- Oncology 132
- Artificial Intelligence 105
- Computer Vision and Pattern Recognition 81
- Civil and Structural Engineering 66
- Biomedical Engineering 54
Countries citing papers authored by Maher I. Rajab
This map shows the geographic impact of Maher I. Rajab'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 Maher I. Rajab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maher I. Rajab more than expected).
Fields of papers citing papers by Maher I. Rajab
This network shows the impact of papers produced by Maher I. Rajab. 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 Maher I. Rajab. The network helps show where Maher I. Rajab may publish in the future.
Co-authorship network of co-authors of Maher I. Rajab
This figure shows the co-authorship network connecting the top 25 collaborators of Maher I. Rajab. A scholar is included among the top collaborators of Maher I. Rajab 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 Maher I. Rajab. Maher I. Rajab is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 40 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | Stabilization and enhancement of microcirculatory video sequences | 3 |
| 6 | 94 | |
| 7 | 9 | |
| 8 | 11 | |
| 9 | 17 | |
| 10 | Analysis of neural network edge pattern detectors in terms of domain functions | 2 |
| 11 | 4 | |
| 12 | 7 | |
| 13 | Feature extraction of epiluminescence microscopic images by iterative segmentation algorithm | 5 |
| 14 | Applications of neural network for optimum asphaltic concrete mixtures | 4 |
| 15 | Determination of optimum bitumen content and Marshall stability using neural networks for asphaltic concrete mixtures | 3 |
| 16 | Application of neural networks analysis in image feature extraction | 1 |
| 17 | 93 |
About Maher I. Rajab
Maher I. Rajab is a scholar working on Biophysics, Oncology and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 300 indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (7 papers), Asphalt Pavement Performance Evaluation (5 papers) and Infrastructure Maintenance and Monitoring (5 papers). The work is most often cited by research in Oncology (132 citations), Biophysics (23 citations) and Computer Vision and Pattern Recognition (81 citations). Maher I. Rajab has collaborated with scholars based in Saudi Arabia, United Kingdom and Japan. Frequent co-authors include Stephen P. Morgan, M.S. Woolfson, Hitoshi Iyatomi, M. Emre Celebi, Gerald Schaefer and John Crowe. Their work appears in journals such as Computerized Medical Imaging and Graphics, Skin Research and Technology and Road Materials and Pavement Design.
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.