Yusuf Aytar
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Biomedical Engineering
- Signal Processing top 5%
- Public Health, Environmental and Occupational Health
- Co-authors
- Andrew ZissermanAntonio TorralbaJonathan TompsonDebidatta DwibediPierre SermanetFerda OfliIngmar WeberCarl Vondrick
- Topics
- Advanced Image and Video Retrieval Techniques (12 papers)Multimodal Machine Learning Applications (8 papers)Domain Adaptation and Few-Shot Learning (7 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsComputer Vision and Image Understanding
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Yusuf Aytar
25 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Computer Vision and Pattern Recognition 837
- Artificial Intelligence 577
- Biomedical Engineering 184
- Signal Processing 109
- Public Health, Environmental and Occupational Health 68
Countries citing papers authored by Yusuf Aytar
This map shows the geographic impact of Yusuf Aytar'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 Yusuf Aytar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yusuf Aytar more than expected).
Fields of papers citing papers by Yusuf Aytar
This network shows the impact of papers produced by Yusuf Aytar. 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 Yusuf Aytar. The network helps show where Yusuf Aytar may publish in the future.
Co-authorship network of co-authors of Yusuf Aytar
This figure shows the co-authorship network connecting the top 25 collaborators of Yusuf Aytar. A scholar is included among the top collaborators of Yusuf Aytar 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 Yusuf Aytar. Yusuf Aytar 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 | 16 | |
| 4 | 1 | |
| 5 | 8 | |
| 6 | 67 | |
| 7 | A Framework for Data-Driven Robotics | 4 |
| 8 | Visual Imitation with a Minimal Adversary | 1 |
| 9 | 229 | |
| 10 | 77 | |
| 11 | 67 | |
| 12 | 86 | |
| 13 | 102 | |
| 14 | 2 | |
| 15 | 5 | |
| 16 | 2 | |
| 17 | 204 | |
| 18 | 55 | |
| 19 | University of Central Florida at TRECVID 2007 Semantic Video Classification and Automatic Search. | 1 |
| 20 | 25 |
About Yusuf Aytar
Yusuf Aytar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Sensory Systems, having authored 25 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (12 papers), Multimodal Machine Learning Applications (8 papers) and Domain Adaptation and Few-Shot Learning (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (837 citations), Artificial Intelligence (577 citations) and Signal Processing (109 citations). Yusuf Aytar has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Andrew Zisserman, Antonio Torralba, Jonathan Tompson, Debidatta Dwibedi, Pierre Sermanet, Ferda Ofli, Ingmar Weber, Carl Vondrick, Lluís Castrejón and Hamed Pirsiavash. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Computer Vision and Image Understanding.
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.