Cem Direkoğlu
Impact in
- Neurology top 2%
- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Video Surveillance and Tracking Methods
Papers in
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- Video Surveillance and Tracking Methods 11
- Medical Image Segmentation Techniques 9
- Human Pose and Action Recognition 7
- Image Retrieval and Classification Techniques 6
- Video Analysis and Summarization 5
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- Anomaly Detection Techniques and Applications 8
- Co-authors
- Melike Şah (14 shared papers)Ali Işın (1 shared paper)Mark Nixon (6 shared papers)Masashi Unoki (3 shared papers)Noel E. O’Connor (7 shared papers)Murat Fahrioğlu (1 shared paper)Michael Manzke (2 shared papers)Rozenn Dahyot (2 shared papers)
In The Last Decade
Cem Direkoğlu
36 papers receiving 916 citations
Cem Direkoğlu's Hit Papers
Peers
Comparison fields: 5 of 108
- Neurology 367
- Computer Vision and Pattern Recognition 564
- Artificial Intelligence 349
- Health Informatics 12
- Signal Processing 88
Countries citing papers authored by Cem Direkoğlu
This map shows the geographic impact of Cem Direkoğlu'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 Cem Direkoğlu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cem Direkoğlu more than expected).
Fields of papers citing papers by Cem Direkoğlu
This network shows the impact of papers produced by Cem Direkoğlu. 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 Cem Direkoğlu. The network helps show where Cem Direkoğlu may publish in the future.
Co-authors
The 25 scholars most cited alongside Cem Direkoğlu, 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 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Review of MRI-based Brain Tumor Image Segmentation Using Deep Learning Methods Hit paper breakdown → | 2016 | 498 |
| 2 | 2023 | 84 | |
| 3 | 2020 | 69 | |
| 4 | 2024 | 50 | |
| 5 | 2017 | 28 | |
| 6 | 2011 | 22 | |
| 7 | 2020 | 20 | |
| 8 | 2023 | 17 | |
| 9 | 2022 | 15 | |
| 10 | 2021 | 13 | |
| 11 | 2008 | 13 | |
| 12 | 2017 | 13 | |
| 13 | 2012 | 13 | |
| 14 | 2013 | 13 | |
| 15 | 2022 | 13 | |
| 16 | 2024 | 12 | |
| 17 | 2006 | 10 | |
| 18 | 2013 | 10 | |
| 19 | 2009 | 9 | |
| 20 | 2010 | 8 |
About Cem Direkoğlu
Cem Direkoğlu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Electrical and Electronic Engineering and Neurology, having authored 42 papers that have together received 983 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (11 papers), Medical Image Segmentation Techniques (9 papers), Anomaly Detection Techniques and Applications (8 papers), Human Pose and Action Recognition (7 papers), Music and Audio Processing (6 papers), Image Retrieval and Classification Techniques (6 papers), Video Analysis and Summarization (5 papers) and Speech and Audio Processing (5 papers). The work is most often cited by research in Neurology (367 citations), Computer Vision and Pattern Recognition (564 citations), Artificial Intelligence (349 citations), Health Informatics (12 citations) and Signal Processing (88 citations). Cem Direkoğlu has collaborated with scholars based in Türkiye, Cyprus and Ireland. Frequent co-authors include Melike Şah, Ali Işın, Mark Nixon, Masashi Unoki, Noel E. O’Connor, Murat Fahrioğlu, Michael Manzke, Rozenn Dahyot, Suzanne Little and David J. Hurley. Their work appears in journals such as IEEE Access, Multimedia Tools and Applications, Neural Computing and Applications, Machine Vision and Applications and Pattern Recognition Letters.
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.