Riaz Ali
Impact in
-
- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Generative Adversarial Networks and Image Synthesis
-
- Radiomics and Machine Learning in Medical Imaging
- Retinal Imaging and Analysis
- COVID-19 diagnosis using AI
Papers in
-
- Advanced Image Processing Techniques 3
- Digital Imaging for Blood Diseases 2
- Image Enhancement Techniques 2
-
- COVID-19 diagnosis using AI 3
- Retinal Imaging and Analysis 2
- Co-authors
- Ping Li (5 shared papers)C. L. Philip Chen (3 shared papers)Yao Shen (3 shared papers)Jian Chen (1 shared paper)Bin Sheng (2 shared papers)Huating Li (2 shared papers)Younhyun Jung (2 shared papers)Jinman Kim (3 shared papers)
In The Last Decade
Riaz Ali
21 papers receiving 362 citations
Peers
Comparison fields: 5 of 64
- Computer Vision and Pattern Recognition 160
- Radiology, Nuclear Medicine and Imaging 86
- Artificial Intelligence 121
- Ophthalmology 26
- Media Technology 27
Countries citing papers authored by Riaz Ali
This map shows the geographic impact of Riaz Ali'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 Riaz Ali with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riaz Ali more than expected).
Fields of papers citing papers by Riaz Ali
This network shows the impact of papers produced by Riaz Ali. 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 Riaz Ali. The network helps show where Riaz Ali may publish in the future.
Co-authors
The 25 scholars most cited alongside Riaz Ali, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 90 | |
| 2 | 2020 | 67 | |
| 3 | 2021 | 63 | |
| 4 | 2021 | 41 | |
| 5 | 2018 | 34 | |
| 6 | 2025 | 15 | |
| 7 | 2025 | 8 | |
| 8 | 2024 | 7 | |
| 9 | 2017 | 6 | |
| 10 | 2024 | 6 | |
| 11 | 2017 | 5 | |
| 12 | 2022 | 4 | |
| 13 | 2015 | 4 | |
| 14 | 2025 | 3 | |
| 15 | 2025 | 3 | |
| 16 | 2025 | 3 | |
| 17 | 2021 | 3 | |
| 18 | 2018 | 3 | |
| 19 | 2020 | 2 | |
| 20 | 2021 | 1 |
About Riaz Ali
Riaz Ali is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Electronic, Optical and Magnetic Materials, Artificial Intelligence and Electrical and Electronic Engineering, having authored 21 papers that have together received 369 indexed citations. Recurring topics across this work include Metamaterials and Metasurfaces Applications (5 papers), COVID-19 diagnosis using AI (3 papers), Advanced Image Processing Techniques (3 papers), Antenna Design and Analysis (3 papers), Retinal Imaging and Analysis (2 papers), Digital Imaging for Blood Diseases (2 papers), Thermal Radiation and Cooling Technologies (2 papers) and Image Enhancement Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (160 citations), Radiology, Nuclear Medicine and Imaging (86 citations), Artificial Intelligence (121 citations), Ophthalmology (26 citations) and Media Technology (27 citations). Riaz Ali has collaborated with scholars based in China, Pakistan and Hong Kong. Frequent co-authors include Ping Li, C. L. Philip Chen, Yao Shen, Jian Chen, Bin Sheng, Huating Li, Younhyun Jung, Bin Sheng, Jinman Kim and Po Yang. Their work appears in journals such as Microchemical Journal, Diamond and Related Materials, PeerJ Computer Science, IEEE Transactions on Image Processing and Chinese Optics Letters.
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.