Ayşegül Dündar
- Computer Vision and Pattern Recognition top 2%
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Hardware and Architecture top 10%
- Computer Networks and Communications
- Co-authors
- Eugenio CulurcielloJonghoon JinBerin MartiniVinayak GokhaleTing-Chun WangZhiding YuAndrew TaoBryan Catanzaro
- Topics
- Generative Adversarial Networks and Image Synthesis (8 papers)Advanced Neural Network Applications (8 papers)Advanced Image and Video Retrieval Techniques (6 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionIEEE Transactions on Neural Networks and Learning Systems
- Partner nations
- United StatesTürkiyeGermany
In The Last Decade
Ayşegül Dündar
21 papers receiving 504 citations
Peers
Comparison fields: 5 of 70
- Computer Vision and Pattern Recognition 384
- Electrical and Electronic Engineering 227
- Artificial Intelligence 137
- Hardware and Architecture 56
- Computer Networks and Communications 23
Countries citing papers authored by Ayşegül Dündar
This map shows the geographic impact of Ayşegül Dündar'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 Ayşegül Dündar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ayşegül Dündar more than expected).
Fields of papers citing papers by Ayşegül Dündar
This network shows the impact of papers produced by Ayşegül Dündar. 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 Ayşegül Dündar. The network helps show where Ayşegül Dündar may publish in the future.
Co-authorship network of co-authors of Ayşegül Dündar
This figure shows the co-authorship network connecting the top 25 collaborators of Ayşegül Dündar. A scholar is included among the top collaborators of Ayşegül Dündar 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 Ayşegül Dündar. Ayşegül Dündar 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 | 22 | |
| 4 | 1 | |
| 5 | 10 | |
| 6 | 0 | |
| 7 | 17 | |
| 8 | 31 | |
| 9 | 1 | |
| 10 | 22 | |
| 11 | Neural FFTs for Universal Texture Image Synthesis | 7 |
| 12 | A new look at clustering through the lens of deep convolutional neural networks | 0 |
| 13 | 82 | |
| 14 | 16 | |
| 15 | Flattened Convolutional Neural Networks for Feedforward Acceleration | 15 |
| 16 | 18 | |
| 17 | 217 | |
| 18 | 27 | |
| 19 | Clustering learning for robotic vision | 1 |
| 20 | 1 |
About Ayşegül Dündar
Ayşegül Dündar is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Geology, having authored 24 papers that have together received 519 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (8 papers), Advanced Neural Network Applications (8 papers) and Advanced Image and Video Retrieval Techniques (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (384 citations), Hardware and Architecture (56 citations) and Artificial Intelligence (137 citations). Ayşegül Dündar has collaborated with scholars based in United States, Türkiye and Germany. Frequent co-authors include Eugenio Culurciello, Jonghoon Jin, Berin Martini, Vinayak Gokhale, Ting-Chun Wang, Zhiding Yu, Andrew Tao, Bryan Catanzaro, Clément Farabet and Mehmet Akif Şahman. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE Transactions on Neural Networks and Learning Systems.
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.