Ahmet İşcen
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Aerospace Engineering
- Media Technology
- Computer Networks and Communications
- Co-authors
- Giorgos ToliasCordelia SchmidYannis AvrithisJack ValmadreOndřej ChumAnurag ArnabFilip RadenovićPhilippe-Henri Gosselin
- Topics
- Advanced Image and Video Retrieval Techniques (7 papers)Image Retrieval and Classification Techniques (4 papers)Multimodal Machine Learning Applications (3 papers)
- Journals
- IEEE Transactions on Image ProcessingMachine Vision and Applications2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- United StatesFranceCzechia
In The Last Decade
Ahmet İşcen
10 papers receiving 200 citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 158
- Artificial Intelligence 104
- Aerospace Engineering 19
- Media Technology 13
- Computer Networks and Communications 5
Countries citing papers authored by Ahmet İşcen
This map shows the geographic impact of Ahmet İşcen'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 Ahmet İşcen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmet İşcen more than expected).
Fields of papers citing papers by Ahmet İşcen
This network shows the impact of papers produced by Ahmet İşcen. 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 Ahmet İşcen. The network helps show where Ahmet İşcen may publish in the future.
Co-authorship network of co-authors of Ahmet İşcen
This figure shows the co-authorship network connecting the top 25 collaborators of Ahmet İşcen. A scholar is included among the top collaborators of Ahmet İşcen 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 Ahmet İşcen. Ahmet İşcen 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 | 10 | |
| 3 | 35 | |
| 4 | 51 | |
| 5 | 4 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 58 | |
| 9 | 39 | |
| 10 | 2 | |
| 11 | 1 |
About Ahmet İşcen
Ahmet İşcen is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 11 papers that have together received 206 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (7 papers), Image Retrieval and Classification Techniques (4 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (158 citations), Artificial Intelligence (104 citations) and Media Technology (13 citations). Ahmet İşcen has collaborated with scholars based in United States, France and Czechia. Frequent co-authors include Giorgos Tolias, Cordelia Schmid, Yannis Avrithis, Jack Valmadre, Ondřej Chum, Anurag Arnab, Filip Radenović, Philippe-Henri Gosselin, Hervé Jeǵou and Alireza Fathi. Their work appears in journals such as IEEE Transactions on Image Processing, Machine Vision and Applications and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.