Mete Özay
- Control and Systems Engineering top 2%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Fatoş T. Yarman VuralH. Vincent PoorIñaki EsnaolaSanjeev R. KulkarniUmberto MichieliÇağlar ŞenarasTakayuki OkataniMarco Toldo
- Topics
- Domain Adaptation and Few-Shot Learning (12 papers)Functional Brain Connectivity Studies (11 papers)Neural Networks and Applications (10 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePhysical Chemistry Chemical PhysicsIEEE Access
- Partner nations
- TürkiyeUnited KingdomJapan
In The Last Decade
Mete Özay
60 papers receiving 986 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Control and Systems Engineering 525
- Computer Networks and Communications 414
- Artificial Intelligence 376
- Electrical and Electronic Engineering 259
- Computer Vision and Pattern Recognition 174
Countries citing papers authored by Mete Özay
This map shows the geographic impact of Mete Özay'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 Mete Özay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mete Özay more than expected).
Fields of papers citing papers by Mete Özay
This network shows the impact of papers produced by Mete Özay. 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 Mete Özay. The network helps show where Mete Özay may publish in the future.
Co-authorship network of co-authors of Mete Özay
This figure shows the co-authorship network connecting the top 25 collaborators of Mete Özay. A scholar is included among the top collaborators of Mete Özay 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 Mete Özay. Mete Özay 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 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 4 | |
| 10 | 0 | |
| 11 | 2 | |
| 12 | 0 | |
| 13 | 2 | |
| 14 | 26 | |
| 15 | 3 | |
| 16 | 9 | |
| 17 | 1 | |
| 18 | 16 | |
| 19 | A New Fuzzy Stacked Generalization Technique for Deep learning and Analysis of its Performance | 4 |
| 20 | 13 |
About Mete Özay
Mete Özay is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 73 papers that have together received 1.0k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (12 papers), Functional Brain Connectivity Studies (11 papers) and Neural Networks and Applications (10 papers). The work is most often cited by research in Control and Systems Engineering (525 citations), Computer Networks and Communications (414 citations) and Artificial Intelligence (376 citations). Mete Özay has collaborated with scholars based in Türkiye, United Kingdom and Japan. Frequent co-authors include Fatoş T. Yarman Vural, H. Vincent Poor, Iñaki Esnaola, Sanjeev R. Kulkarni, Umberto Michieli, Çağlar Şenaras, Takayuki Okatani, Marco Toldo, Jiwei Tian and Hongli Xu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Physical Chemistry Chemical Physics and IEEE Access.
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.