Amjad Rehman
- Computer Vision and Pattern Recognition top 0.1%
- Artificial Intelligence top 0.1%
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Neurology top 0.2%
- Computer Networks and Communications top 1%
- Co-authors
- Tanzila SabaZahid MehmoodMuhammad Attique KhanSaeed Ali BahajSajid IqbalMohd Shafry Mohd RahimHoshang KolivandUsman Tariq
- Topics
- AI in cancer detection (46 papers)IoT and Edge/Fog Computing (37 papers)Handwritten Text Recognition Techniques (35 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- Saudi ArabiaPakistanMalaysia
In The Last Decade
Amjad Rehman
383 papers receiving 10.9k citations
Hit Papers
Peers
Comparison fields: 5 of 196
- Computer Vision and Pattern Recognition 5.1k
- Artificial Intelligence 4.2k
- Radiology, Nuclear Medicine and Imaging 2.2k
- Neurology 2.0k
- Computer Networks and Communications 1.3k
Countries citing papers authored by Amjad Rehman
This map shows the geographic impact of Amjad Rehman'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 Amjad Rehman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amjad Rehman more than expected).
Fields of papers citing papers by Amjad Rehman
This network shows the impact of papers produced by Amjad Rehman. 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 Amjad Rehman. The network helps show where Amjad Rehman may publish in the future.
Co-authorship network of co-authors of Amjad Rehman
This figure shows the co-authorship network connecting the top 25 collaborators of Amjad Rehman. A scholar is included among the top collaborators of Amjad Rehman 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 Amjad Rehman. Amjad Rehman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 11 | |
| 7 | 28 | |
| 8 | 5 | |
| 9 | 84 | |
| 10 | 17 | |
| 11 | 38 | |
| 12 | Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologistsbreakdown → | 306 |
| 13 | 35 | |
| 14 | 74 | |
| 15 | 3D bones segmentation based on CT images visualization | 47 |
| 16 | Ear biometrics for human classification based on region features mining | 37 |
| 17 | Outdoor 3D illumination in real time environments: a novel approach | 1 |
| 18 | 1 | |
| 19 | 7 | |
| 20 | 2 |
About Amjad Rehman
Amjad Rehman is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Neurology, having authored 397 papers that have together received 11.6k indexed citations. Recurring topics across this work include AI in cancer detection (46 papers), IoT and Edge/Fog Computing (37 papers) and Handwritten Text Recognition Techniques (35 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (5.1k citations), Neurology (2.0k citations) and Artificial Intelligence (4.2k citations). Amjad Rehman has collaborated with scholars based in Saudi Arabia, Pakistan and Malaysia. Frequent co-authors include Tanzila Saba, Zahid Mehmood, Muhammad Attique Khan, Saeed Ali Bahaj, Sajid Iqbal, Mohd Shafry Mohd Rahim, Hoshang Kolivand, Usman Tariq, Khalid Haseeb and Muhammad Sharif. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.