Müge Sayıt
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 10%
- Sociology and Political Science
- Electrical and Electronic Engineering
- Co-authors
- Stuart ClaymanCornelius HellgeYagiz KaymakGeylani KardaşHasan BulutAli C. BegenHüseyin Uğur YıldızBülent Tavlı
- Topics
- Image and Video Quality Assessment (36 papers)Caching and Content Delivery (26 papers)Video Coding and Compression Technologies (17 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionComputer Networks and Communications
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessComputer Networks
- Partner nations
- TürkiyeUnited KingdomGermany
In The Last Decade
Müge Sayıt
46 papers receiving 245 citations
Peers
Comparison fields: 5 of 22
- Computer Networks and Communications 186
- Computer Vision and Pattern Recognition 170
- Signal Processing 94
- Sociology and Political Science 35
- Electrical and Electronic Engineering 35
Countries citing papers authored by Müge Sayıt
This map shows the geographic impact of Müge Sayıt'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 Müge Sayıt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Müge Sayıt more than expected).
Fields of papers citing papers by Müge Sayıt
This network shows the impact of papers produced by Müge Sayıt. 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 Müge Sayıt. The network helps show where Müge Sayıt may publish in the future.
Co-authorship network of co-authors of Müge Sayıt
This figure shows the co-authorship network connecting the top 25 collaborators of Müge Sayıt. A scholar is included among the top collaborators of Müge Sayıt 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 Müge Sayıt. Müge Sayıt 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 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 4 | |
| 9 | 9 | |
| 10 | 3 | |
| 11 | 11 | |
| 12 | 4 | |
| 13 | 6 | |
| 14 | 8 | |
| 15 | 2 | |
| 16 | 9 | |
| 17 | 6 | |
| 18 | 24 | |
| 19 | 3 | |
| 20 | 1 |
About Müge Sayıt
Müge Sayıt is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications, having authored 49 papers that have together received 252 indexed citations. Recurring topics across this work include Image and Video Quality Assessment (36 papers), Caching and Content Delivery (26 papers) and Video Coding and Compression Technologies (17 papers). The work is most often cited by research in Signal Processing (94 citations), Computer Vision and Pattern Recognition (170 citations) and Computer Networks and Communications (186 citations). Müge Sayıt has collaborated with scholars based in Türkiye, United Kingdom and Germany. Frequent co-authors include Stuart Clayman, Cornelius Hellge, Yagiz Kaymak, Geylani Kardaş, Hasan Bulut, Ali C. Begen, Hüseyin Uğur Yıldız, Bülent Tavlı, Miguel Rio and David Griffin. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Computer Networks.
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.