Mohammad Reza Faraji
- Computer Vision and Pattern Recognition top 5%
- Health top 10%
- Modeling and Simulation top 5%
- Infectious Diseases
- Artificial Intelligence
- Co-authors
- Xiaojun QiMoosa TatarFernando A. WilsonM.H. Fazel ZarandiMahdi KarbasianJosé A. PagánAustin M. JensenKatherine M. Keyes
- Topics
- Face and Expression Recognition (6 papers)Face recognition and analysis (5 papers)Image and Video Quality Assessment (4 papers)
- Partner nations
- United StatesIranGermany
In The Last Decade
Mohammad Reza Faraji
17 papers receiving 359 citations
Peers
Comparison fields: 5 of 96
- Computer Vision and Pattern Recognition 152
- Health 69
- Modeling and Simulation 54
- Infectious Diseases 51
- Artificial Intelligence 42
Countries citing papers authored by Mohammad Reza Faraji
This map shows the geographic impact of Mohammad Reza Faraji'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 Mohammad Reza Faraji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Reza Faraji more than expected).
Fields of papers citing papers by Mohammad Reza Faraji
This network shows the impact of papers produced by Mohammad Reza Faraji. 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 Mohammad Reza Faraji. The network helps show where Mohammad Reza Faraji may publish in the future.
Co-authorship network of co-authors of Mohammad Reza Faraji
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Reza Faraji. A scholar is included among the top collaborators of Mohammad Reza Faraji 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 Mohammad Reza Faraji. Mohammad Reza Faraji 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 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 34 | |
| 9 | 28 | |
| 10 | 4 | |
| 11 | 3 | |
| 12 | 8 | |
| 13 | 40 | |
| 14 | 10 | |
| 15 | 22 | |
| 16 | 26 | |
| 17 | 31 | |
| 18 | 8 | |
| 19 | 35 | |
| 20 | An Exponential Cluster Validity Index for Fuzzy Clustering with Crisp and Fuzzy Data | 23 |
About Mohammad Reza Faraji
Mohammad Reza Faraji is a scholar working on Modeling and Simulation, Computer Vision and Pattern Recognition and Health, having authored 21 papers that have together received 370 indexed citations. Recurring topics across this work include Face and Expression Recognition (6 papers), Face recognition and analysis (5 papers) and Image and Video Quality Assessment (4 papers). The work is most often cited by research in Modeling and Simulation (54 citations), Health (69 citations) and Computer Vision and Pattern Recognition (152 citations). Mohammad Reza Faraji has collaborated with scholars based in United States, Iran and Germany. Frequent co-authors include Xiaojun Qi, Moosa Tatar, Fernando A. Wilson, M.H. Fazel Zarandi, Mahdi Karbasian, José A. Pagán, Austin M. Jensen, Katherine M. Keyes, Mohammad S. Jalali and Ryo Suzuki. Their work appears in journals such as Scientific Reports, Sustainability and Neurocomputing.
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.