Erhan Gökçay
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 10%
- Electrical and Electronic Engineering
- Computer Networks and Communications
- Co-authors
- José C. Prı́ncipeDidem Gökçayİlkay UlusoyJack DongarraMichelle MillerJoel R. StilesHenri CasanovaRich Wolski
- Topics
- Chaos-based Image/Signal Encryption (4 papers)Neural Networks and Applications (4 papers)Face and Expression Recognition (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceExpert Systems with ApplicationsInformation Sciences
- Partner nations
- TürkiyeUnited States
In The Last Decade
Erhan Gökçay
11 papers receiving 278 citations
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 158
- Computer Vision and Pattern Recognition 111
- Signal Processing 54
- Electrical and Electronic Engineering 32
- Computer Networks and Communications 30
Countries citing papers authored by Erhan Gökçay
This map shows the geographic impact of Erhan Gökçay'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 Erhan Gökçay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erhan Gökçay more than expected).
Fields of papers citing papers by Erhan Gökçay
This network shows the impact of papers produced by Erhan Gökçay. 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 Erhan Gökçay. The network helps show where Erhan Gökçay may publish in the future.
Co-authorship network of co-authors of Erhan Gökçay
This figure shows the co-authorship network connecting the top 25 collaborators of Erhan Gökçay. A scholar is included among the top collaborators of Erhan Gökçay 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 Erhan Gökçay. Erhan Gökçay 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 | 2 | |
| 3 | 8 | |
| 4 | 16 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 11 | |
| 11 | 18 | |
| 12 | 204 | |
| 13 | 7 | |
| 14 | 21 | |
| 15 | A new clustering algorithm for segmentation of magnetic resonance images | 2 |
About Erhan Gökçay
Erhan Gökçay is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Hardware and Architecture, having authored 15 papers that have together received 292 indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (4 papers), Neural Networks and Applications (4 papers) and Face and Expression Recognition (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (111 citations), Signal Processing (54 citations) and Artificial Intelligence (158 citations). Erhan Gökçay has collaborated with scholars based in Türkiye and United States. Frequent co-authors include José C. Prı́ncipe, Didem Gökçay, İlkay Ulusoy, Jack Dongarra, Michelle Miller, Joel R. Stiles, Henri Casanova, Rich Wolski, Graziano Obertelli and Marcio Faerman. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and Information Sciences.
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.