Mahmut Kaya
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- Advanced Neural Network Applications 2
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications 4
- Data Stream Mining Techniques 2
- Text and Document Classification Technologies 2
- Advanced Clustering Algorithms Research 2
- Media Technology top 5%
- Signal Processing top 10%
- Speech and Audio Processing 2
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- Gene expression and cancer classification 2
- Machine Learning in Bioinformatics 2
- Journals
- Applied Sciences (2 papers)Measurement Science and Technology (1 paper)Neural Computing and Applications (1 paper)
- Partner nations
- TürkiyeChinaSaudi Arabia
In The Last Decade
Mahmut Kaya
21 papers receiving 636 citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Computer Vision and Pattern Recognition 270
- Artificial Intelligence 259
- Media Technology 59
- Signal Processing 64
- Industrial and Manufacturing Engineering 45
Countries citing papers authored by Mahmut Kaya
This map shows the geographic impact of Mahmut Kaya'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 Mahmut Kaya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahmut Kaya more than expected).
Fields of papers citing papers by Mahmut Kaya
This network shows the impact of papers produced by Mahmut Kaya. 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 Mahmut Kaya. The network helps show where Mahmut Kaya may publish in the future.
Co-authorship network
The 7 scholars most cited alongside Mahmut Kaya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 6 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 2 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 4 | |
| 10 | 2022 | 23 | |
| 11 | 2022 | 4 | |
| 12 | 2022 | 21 | |
| 13 | Trends in Outbreak Detection in Early Stage by Using Machine Learning Approaches | 2021 | 4 |
| 14 | Deep Metric Learning: A Surveybreakdown → | 2019 | 436 |
| 15 | 2018 | 141 | |
| 16 | 2017 | 3 | |
| 17 | 2016 | 3 | |
| 18 | 2015 | 1 | |
| 19 | 2014 | 6 | |
| 20 | 2013 | 1 |
About Mahmut Kaya
Mahmut Kaya is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 667 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), Gene expression and cancer classification (2 papers), Machine Learning in Bioinformatics (2 papers), Speech and Audio Processing (2 papers), Data Stream Mining Techniques (2 papers), Advanced Neural Network Applications (2 papers), Text and Document Classification Technologies (2 papers) and Advanced Clustering Algorithms Research (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (270 citations), Artificial Intelligence (259 citations) and Media Technology (59 citations). Mahmut Kaya has collaborated with scholars based in Türkiye, China and Saudi Arabia. Frequent co-authors include Hasan Şakir Bılge, Yılmaz Kaya, Anıl Utku, Bekir Sami Yilbaş, Ömer Keleş, Abdul Qader and Oktay Yıldız. Their work appears in journals such as Applied Sciences, Measurement Science and Technology and Neural Computing and 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.