Pinar Akyazi
- Artificial Intelligence top 2%
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 10%
- Experimental and Cognitive Psychology
- Media Technology
- Co-authors
- Touradj EbrahimiAriya RastrowOndřej GlembekSamuel ThomasKai FengMartin KarafiátLukáš BurgetMohit Agarwal
- Topics
- Image and Signal Denoising Methods (5 papers)Advanced Data Compression Techniques (5 papers)Advanced Vision and Imaging (4 papers)
- Journals
- Computer Speech & LanguageInfoscience (Ecole Polytechnique Fédérale de Lausanne)Electronic Imaging
- Partner nations
- SwitzerlandCzechiaUnited States
In The Last Decade
Pinar Akyazi
17 papers receiving 526 citations
Peers
Comparison fields: 5 of 51
- Artificial Intelligence 474
- Signal Processing 427
- Computer Vision and Pattern Recognition 131
- Experimental and Cognitive Psychology 28
- Media Technology 12
Countries citing papers authored by Pinar Akyazi
This map shows the geographic impact of Pinar Akyazi'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 Pinar Akyazi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pinar Akyazi more than expected).
Fields of papers citing papers by Pinar Akyazi
This network shows the impact of papers produced by Pinar Akyazi. 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 Pinar Akyazi. The network helps show where Pinar Akyazi may publish in the future.
Co-authorship network of co-authors of Pinar Akyazi
This figure shows the co-authorship network connecting the top 25 collaborators of Pinar Akyazi. A scholar is included among the top collaborators of Pinar Akyazi 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 Pinar Akyazi. Pinar Akyazi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 23 | |
| 2 | Learning-Based Image Compression using Convolutional Autoencoder and Wavelet Decomposition | 10 |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 7 | |
| 6 | 16 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 4 | |
| 10 | 38 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 124 | |
| 14 | 210 | |
| 15 | 19 | |
| 16 | 123 | |
| 17 | 20 |
About Pinar Akyazi
Pinar Akyazi is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 17 papers that have together received 606 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (5 papers), Advanced Data Compression Techniques (5 papers) and Advanced Vision and Imaging (4 papers). The work is most often cited by research in Signal Processing (427 citations), Artificial Intelligence (474 citations) and Computer Vision and Pattern Recognition (131 citations). Pinar Akyazi has collaborated with scholars based in Switzerland, Czechia and United States. Frequent co-authors include Touradj Ebrahimi, Ariya Rastrow, Ondřej Glembek, Samuel Thomas, Kai Feng, Martin Karafiát, Lukáš Burget, Mohit Agarwal, Richard C. Rose and Arnab Ghoshal. Their work appears in journals such as Computer Speech & Language, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and Electronic Imaging.
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.