Buket D. Barkana
- Artificial Intelligence top 5%
- Oncology
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Co-authors
- Miad FaezipourOmar Abuzaghlehİnci SarıçiçekMohammad DaneshzandJingcheng ZhouBurak UzkentJidong YangMuder Almiani
- Topics
- Speech and Audio Processing (23 papers)Music and Audio Processing (13 papers)Speech Recognition and Synthesis (13 papers)
- Partner nations
- United StatesTürkiyeEgypt
In The Last Decade
Buket D. Barkana
63 papers receiving 803 citations
Peers
Comparison fields: 5 of 116
- Artificial Intelligence 362
- Oncology 225
- Computer Vision and Pattern Recognition 211
- Signal Processing 209
- Radiology, Nuclear Medicine and Imaging 118
Countries citing papers authored by Buket D. Barkana
This map shows the geographic impact of Buket D. Barkana'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 Buket D. Barkana with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Buket D. Barkana more than expected).
Fields of papers citing papers by Buket D. Barkana
This network shows the impact of papers produced by Buket D. Barkana. 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 Buket D. Barkana. The network helps show where Buket D. Barkana may publish in the future.
Co-authorship network of co-authors of Buket D. Barkana
This figure shows the co-authorship network connecting the top 25 collaborators of Buket D. Barkana. A scholar is included among the top collaborators of Buket D. Barkana 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 Buket D. Barkana. Buket D. Barkana 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 | 0 | |
| 3 | 6 | |
| 4 | 2 | |
| 5 | 17 | |
| 6 | 6 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 24 | |
| 10 | 5 | |
| 11 | 26 | |
| 12 | 25 | |
| 13 | A Portable Real-Time Noninvasice Skin Lesion Analysis System to Assist in Melanoma Early Detection and Prevention | 2 |
| 14 | 55 | |
| 15 | 3 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | Improving teaching tools and techniques of teaching graduate engineering courses based on students’ learning styles and multiple intelligences | 1 |
| 19 | 8 | |
| 20 | A comparison of the Common Vector and the discriminative Common Vector methods for face recognition | 8 |
About Buket D. Barkana
Buket D. Barkana is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 69 papers that have together received 860 indexed citations. Recurring topics across this work include Speech and Audio Processing (23 papers), Music and Audio Processing (13 papers) and Speech Recognition and Synthesis (13 papers). The work is most often cited by research in Signal Processing (209 citations), Artificial Intelligence (362 citations) and Computer Vision and Pattern Recognition (211 citations). Buket D. Barkana has collaborated with scholars based in United States, Türkiye and Egypt. Frequent co-authors include Miad Faezipour, Omar Abuzaghleh, İnci Sarıçiçek, Mohammad Daneshzand, Jingcheng Zhou, Burak Uzkent, Jidong Yang, Muder Almiani, Hakan Çevıkalp and Atalay Barkana. Their work appears in journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.
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.