Hossein Nejati
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Oncology
- Signal Processing top 10%
- Cognitive Neuroscience
- Co-authors
- Ngai‐Man CheungVictor PomponiuTerence SimDong GuoRui LiuElisa Martínez-MarroquínLi ZhangThanh-Toan Do
- Topics
- Face Recognition and Perception (7 papers)Face recognition and analysis (7 papers)EEG and Brain-Computer Interfaces (4 papers)
- Partner nations
- SingaporeUnited StatesIran
In The Last Decade
Hossein Nejati
21 papers receiving 276 citations
Peers
Comparison fields: 5 of 73
- Artificial Intelligence 112
- Computer Vision and Pattern Recognition 94
- Oncology 72
- Signal Processing 53
- Cognitive Neuroscience 38
Countries citing papers authored by Hossein Nejati
This map shows the geographic impact of Hossein Nejati'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 Hossein Nejati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hossein Nejati more than expected).
Fields of papers citing papers by Hossein Nejati
This network shows the impact of papers produced by Hossein Nejati. 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 Hossein Nejati. The network helps show where Hossein Nejati may publish in the future.
Co-authorship network of co-authors of Hossein Nejati
This figure shows the co-authorship network connecting the top 25 collaborators of Hossein Nejati. A scholar is included among the top collaborators of Hossein Nejati 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 Hossein Nejati. Hossein Nejati is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 9 | |
| 3 | 10 | |
| 4 | 20 | |
| 5 | 12 | |
| 6 | 21 | |
| 7 | 18 | |
| 8 | 2 | |
| 9 | 4 | |
| 10 | 0 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 6 | |
| 14 | 7 | |
| 15 | 1 | |
| 16 | Wonder Ears: Identification of Identical Twins from Ear Images | 41 |
| 17 | 3 | |
| 18 | 2 | |
| 19 | THE PREVALENCE OF HEPATITIS B, HEPATITIS C AND THEIR RISK FACTORS IN TRANSIT HEAVY VEHICLE DRIVERSIN ISFAHAN, IRAN | 1 |
| 20 | 7 |
About Hossein Nejati
Hossein Nejati is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Health Information Management, having authored 22 papers that have together received 286 indexed citations. Recurring topics across this work include Face Recognition and Perception (7 papers), Face recognition and analysis (7 papers) and EEG and Brain-Computer Interfaces (4 papers). The work is most often cited by research in Signal Processing (53 citations), Computer Vision and Pattern Recognition (94 citations) and Artificial Intelligence (112 citations). Hossein Nejati has collaborated with scholars based in Singapore, United States and Iran. Frequent co-authors include Ngai‐Man Cheung, Victor Pomponiu, Terence Sim, Dong Guo, Rui Liu, Elisa Martínez-Marroquín, Li Zhang, Thanh-Toan Do, Yiren Zhou and Kleovoulos Tsourides. Their work appears in journals such as IEEE Signal Processing Magazine, Biological Psychology and Image and Vision Computing.
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.