Süreyya Akyüz

412 citations
30 papers · 217 · h-index 10

Impact in

    • Advanced Optimization Algorithms Research
    • Neural Networks and Applications
    • Machine Learning and Data Classification
    • Imbalanced Data Classification Techniques
    • Metaheuristic Optimization Algorithms Research

Papers in

Süreyya Akyüz

27 papers receiving 211 citations

Peers

Süreyya Akyüz
Comparison fields: 5 of 85
  • Numerical Analysis 14
  • Artificial Intelligence 80
  • Management Science and Operations Research 25
  • Computational Theory and Mathematics 18
  • Management Information Systems 9
Replace Manomita Chakraborty with:
Manomita Chakraborty India
P.N. Robillard Canada
Maslina Zolkepli Malaysia
David Issa Mattos Sweden
César Mattos Brazil
Weiping Ding China
Luiz Alberto Vieira Dias Brazil
Gada Kadoda United Kingdom
Alamsyah Alamsyah Indonesia
Süreyya Akyüz relative to Manomita Chakraborty India Manomita Chakraborty's profile →
Citations per field
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Manomita Chakraborty · 1×
Citations per year

Countries citing papers authored by Süreyya Akyüz

Since Specialization
Citations

This map shows the geographic impact of Süreyya Akyüz'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 Süreyya Akyüz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Süreyya Akyüz more than expected).

Fields of papers citing papers by Süreyya Akyüz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Süreyya Akyüz. 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 Süreyya Akyüz. The network helps show where Süreyya Akyüz may publish in the future.

Co-authors

The 24 scholars most cited alongside Süreyya Akyüz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Süreyya Akyüz Line = papers co-authored together Süreyya Akyüz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201925
2 200822
3 201422
4 202316
5 200916
6 201115
7 201014
8 202213
9 201912
10 200911
11 20169
12 20088
13
Medical Image Retrieval and Automatic Annotation: VPA-SABANCI at ImageCLEF 2009
20095
14 20205
15 20155
16 20213
17 20093
18 20252
19 20232
20 20222

About Süreyya Akyüz

Süreyya Akyüz is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Cognitive Neuroscience and Control and Systems Engineering, having authored 30 papers that have together received 217 indexed citations. Recurring topics across this work include Face and Expression Recognition (6 papers), Neural Networks and Applications (5 papers), Anomaly Detection Techniques and Applications (3 papers), Machine Learning and Data Classification (3 papers), Data Stream Mining Techniques (3 papers), Advanced Clustering Algorithms Research (2 papers), Sparse and Compressive Sensing Techniques (2 papers) and Financial Distress and Bankruptcy Prediction (2 papers). The work is most often cited by research in Numerical Analysis (14 citations), Artificial Intelligence (80 citations), Management Science and Operations Research (25 citations), Computational Theory and Mathematics (18 citations) and Management Information Systems (9 citations). Süreyya Akyüz has collaborated with scholars based in Türkiye, Germany and United Kingdom. Frequent co-authors include Gerhard‐Wilhelm Weber, Birsen Eygi Erdoğan, Terry Windeatt, Erik Kropat, Pakize Taylan, Christoph M. Friedrich, Yeşim Aydın Son, Semih Kuter, Zümrüt B. Ögel and John Shawe‐Taylor. Their work appears in journals such as Information Sciences, Machine Learning, IEEE Transactions on Fuzzy Systems, Neural Networks and Top.

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.

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