Can Eyüpoğlu
Impact in
- Polymers and Plastics top 10%
- Natural Fiber Reinforced Composites
-
- Artificial Intelligence in Healthcare
Papers in
-
- Privacy-Preserving Technologies in Data 5
- AI in cancer detection 5
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- Natural Fiber Reinforced Composites 7
- Co-authors
- Şeyda Eyüpoğlu (17 shared papers)Yavuz Erdem (9 shared papers)Nigar Merdan (13 shared papers)Muhammed Ali Aydın (3 shared papers)Abdül Halim Zaim (2 shared papers)Ahmet Sertbaş (2 shared papers)Mustafa Cem KASAPBAŞI (1 shared paper)Oktay Karakuş (4 shared papers)
- Journals
- Coloration Technology (2 papers)IEEE Access (2 papers)Fibers and Polymers (2 papers)Textile Research Journal (1 paper)Journal of Applied Biomedicine (1 paper)
- Partner nations
- TürkiyeUnited KingdomUnited States
In The Last Decade
Can Eyüpoğlu
47 papers receiving 453 citations
Peers
Comparison fields: 5 of 83
- Polymers and Plastics 102
- Health Information Management 31
- Biomaterials 82
- Building and Construction 76
- Health Informatics 7
Countries citing papers authored by Can Eyüpoğlu
This map shows the geographic impact of Can Eyüpoğlu'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 Can Eyüpoğlu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Eyüpoğlu more than expected).
Fields of papers citing papers by Can Eyüpoğlu
This network shows the impact of papers produced by Can Eyüpoğlu. 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 Can Eyüpoğlu. The network helps show where Can Eyüpoğlu may publish in the future.
Co-authors
The 14 scholars most cited alongside Can Eyüpoğlu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 54 | |
| 2 | 2018 | 53 | |
| 3 | 2019 | 32 | |
| 4 | 2024 | 23 | |
| 5 | 2023 | 23 | |
| 6 | 2022 | 22 | |
| 7 | 2023 | 20 | |
| 8 | 2022 | 19 | |
| 9 | 2017 | 19 | |
| 10 | 2020 | 17 | |
| 11 | 2024 | 17 | |
| 12 | 2018 | 14 | |
| 13 | 2022 | 14 | |
| 14 | 2020 | 11 | |
| 15 | 2017 | 9 | |
| 16 | 2018 | 9 | |
| 17 | 2019 | 8 | |
| 18 | 2015 | 8 | |
| 19 | 2015 | 8 | |
| 20 | 2023 | 7 |
About Can Eyüpoğlu
Can Eyüpoğlu is a scholar working on Artificial Intelligence, Polymers and Plastics, Building and Construction, Computer Vision and Pattern Recognition and Biomaterials, having authored 56 papers that have together received 468 indexed citations. Recurring topics across this work include Dyeing and Modifying Textile Fibers (8 papers), Natural Fiber Reinforced Composites (7 papers), Advanced Cellulose Research Studies (6 papers), Advanced Neural Network Applications (5 papers), Privacy-Preserving Technologies in Data (5 papers), AI in cancer detection (5 papers), melanin and skin pigmentation (4 papers) and Artificial Intelligence in Healthcare (4 papers). The work is most often cited by research in Polymers and Plastics (102 citations), Health Information Management (31 citations), Biomaterials (82 citations), Building and Construction (76 citations) and Health Informatics (7 citations). Can Eyüpoğlu has collaborated with scholars based in Türkiye, United Kingdom and United States. Frequent co-authors include Şeyda Eyüpoğlu, Yavuz Erdem, Nigar Merdan, Muhammed Ali Aydın, Abdül Halim Zaim, Ahmet Sertbaş, Mustafa Cem KASAPBAŞI, Oktay Karakuş, Dilek Kut and Ahmet Onur Girişgin. Their work appears in journals such as Coloration Technology, IEEE Access, Fibers and Polymers, Textile Research Journal and Journal of Applied Biomedicine.
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.