Ferhat Özgür Çatak
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Information Systems top 5%
- Electrical and Electronic Engineering
- Co-authors
- Murat KuzluÜmit CaliSalih SarpJaved AhmedDevrim ÜnalÖzgur GülerMohammad HammoudehAbdulla Al‐Ali
- Topics
- Adversarial Robustness in Machine Learning (19 papers)Anomaly Detection Techniques and Applications (13 papers)Wireless Signal Modulation Classification (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessSensors
- Partner nations
- NorwayTürkiyeUnited States
In The Last Decade
Ferhat Özgür Çatak
54 papers receiving 710 citations
Peers
Comparison fields: 5 of 94
- Artificial Intelligence 422
- Computer Networks and Communications 254
- Signal Processing 203
- Information Systems 188
- Electrical and Electronic Engineering 89
Countries citing papers authored by Ferhat Özgür Çatak
This map shows the geographic impact of Ferhat Özgür Çatak'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 Ferhat Özgür Çatak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ferhat Özgür Çatak more than expected).
Fields of papers citing papers by Ferhat Özgür Çatak
This network shows the impact of papers produced by Ferhat Özgür Çatak. 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 Ferhat Özgür Çatak. The network helps show where Ferhat Özgür Çatak may publish in the future.
Co-authorship network of co-authors of Ferhat Özgür Çatak
This figure shows the co-authorship network connecting the top 25 collaborators of Ferhat Özgür Çatak. A scholar is included among the top collaborators of Ferhat Özgür Çatak 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 Ferhat Özgür Çatak. Ferhat Özgür Çatak 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 | 2 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 42 | |
| 9 | 0 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 12 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 22 | |
| 16 | 3 | |
| 17 | 10 | |
| 18 | 3 | |
| 19 | 9 | |
| 20 | 19 |
About Ferhat Özgür Çatak
Ferhat Özgür Çatak is a scholar working on Artificial Intelligence, Signal Processing and Health Informatics, having authored 61 papers that have together received 741 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (19 papers), Anomaly Detection Techniques and Applications (13 papers) and Wireless Signal Modulation Classification (12 papers). The work is most often cited by research in Health Informatics (29 citations), Signal Processing (203 citations) and Artificial Intelligence (422 citations). Ferhat Özgür Çatak has collaborated with scholars based in Norway, Türkiye and United States. Frequent co-authors include Murat Kuzlu, Ümit Cali, Salih Sarp, Javed Ahmed, Devrim Ünal, Özgur Güler, Mohammad Hammoudeh, Abdulla Al‐Ali, M. Kemal Güllü and Tao Yue. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.
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.