Zümray Dokur

1.7k total citations
58 papers, 1.3k citations indexed

About

Zümray Dokur is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zümray Dokur has authored 58 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Signal Processing, 20 papers in Artificial Intelligence and 19 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zümray Dokur's work include EEG and Brain-Computer Interfaces (15 papers), Blind Source Separation Techniques (14 papers) and Neural Networks and Applications (14 papers). Zümray Dokur is often cited by papers focused on EEG and Brain-Computer Interfaces (15 papers), Blind Source Separation Techniques (14 papers) and Neural Networks and Applications (14 papers). Zümray Dokur collaborates with scholars based in Türkiye and United States. Zümray Dokur's co-authors include Tamer Ölmez, Zafer İşcan, Tamer Demıralp, E. Yazgan, Okan K. Ersoy, Mehmet Korürek, Mehmet Sezgin, Mustafa Çetın, Nerses Bebek and Adil Deniz Duru and has published in prestigious journals such as Expert Systems with Applications, Sensors and Applied Soft Computing.

In The Last Decade

Zümray Dokur

56 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zümray Dokur Türkiye 19 444 425 347 332 275 58 1.3k
Samit Ari India 22 563 1.3× 603 1.4× 345 1.0× 217 0.7× 379 1.4× 100 1.6k
Shivnarayan Patidar India 14 656 1.5× 503 1.2× 204 0.6× 405 1.2× 80 0.3× 28 1.1k
Yakup Kutlu Türkiye 15 352 0.8× 333 0.8× 286 0.8× 199 0.6× 79 0.3× 60 978
Udit Satija India 19 515 1.2× 664 1.6× 227 0.7× 273 0.8× 113 0.4× 75 1.5k
J. S. Sahambi India 15 428 1.0× 544 1.3× 84 0.2× 178 0.5× 201 0.7× 38 988
Kuang Chua Chua Singapore 17 549 1.2× 462 1.1× 98 0.3× 216 0.7× 368 1.3× 31 1.6k
Lim Choo Min Singapore 19 719 1.6× 728 1.7× 166 0.5× 219 0.7× 535 1.9× 44 2.0k
Ramesh Kumar Sunkaria India 18 350 0.8× 558 1.3× 112 0.3× 100 0.3× 144 0.5× 94 956
Ahmad Ayatollahi Iran 18 237 0.5× 173 0.4× 59 0.2× 181 0.5× 288 1.0× 97 1.2k
G. Swapna India 13 696 1.6× 453 1.1× 70 0.2× 339 1.0× 99 0.4× 16 1.5k

Countries citing papers authored by Zümray Dokur

Since Specialization
Citations

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

Fields of papers citing papers by Zümray Dokur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zümray Dokur

This figure shows the co-authorship network connecting the top 25 collaborators of Zümray Dokur. A scholar is included among the top collaborators of Zümray Dokur 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 Zümray Dokur. Zümray Dokur is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dokur, Zümray, et al.. (2024). Classification of brain strokes using divergence-based convolutional neural networks. Biomedical Signal Processing and Control. 93. 106193–106193. 3 indexed citations
2.
Ölmez, Tamer, et al.. (2024). Performance Improvement with Reduced Number of Channels in Motor Imagery BCI System. Sensors. 25(1). 120–120. 2 indexed citations
3.
Ölmez, Tamer, et al.. (2021). Classification of left and right hand motor imagery EEG signals by using deep neural networks. International Journal of Applied Mathematics Electronics and Computers. 9(4). 85–90. 3 indexed citations
4.
Duru, Adil Deniz, et al.. (2021). Neurological effects of long‐term diet on obese and overweight individuals: An electroencephalogram and event‐related potential study. Computational Intelligence. 38(3). 1163–1182. 3 indexed citations
5.
Dokur, Zümray, et al.. (2019). X-Ray Chest Image Classification by A Small-Sized Convolutional Neural Network. Digital Collections portal (Koç University). 1–5. 32 indexed citations
6.
Dokur, Zümray, et al.. (2019). Motor Imagery Based EEG Classification by Using Common Spatial Patterns and Convolutional Neural Networks. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1–4. 15 indexed citations
7.
Dokur, Zümray, et al.. (2016). Protein Fold Recognition Using Self-Organizing Map Neural Network. Current Bioinformatics. 11(4). 451–458. 3 indexed citations
8.
Dokur, Zümray, et al.. (2014). Protein Fold Classification using Kohonen's Self-Organizing Map.. 903–911. 2 indexed citations
9.
Dokur, Zümray, et al.. (2008). Segmentation of S1–S2 sounds in phonocardiogram records using wavelet energies. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1–6. 10 indexed citations
10.
Dokur, Zümray, et al.. (2007). An incremental neural network for tissue segmentation in ultrasound images. Computer Methods and Programs in Biomedicine. 85(3). 187–195. 17 indexed citations
11.
Dokur, Zümray, et al.. (2005). Segmentation of ultrasound images by using an incremental self-organized map. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 3. 2638–2640. 9 indexed citations
12.
Sezgin, Mehmet, Zümray Dokur, Tamer Ölmez, & Mehmet Korürek. (2005). Classification of respiratory sounds by using an artificial neural network. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1. 697–699. 10 indexed citations
13.
Dokur, Zümray, et al.. (2004). Segmentation of remote-sensing images by incremental neural network. Pattern Recognition Letters. 26(8). 1096–1104. 19 indexed citations
14.
Dokur, Zümray, et al.. (2004). Segmentation of ultrasound images by using wavelet transform. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 7. 657–659. 3 indexed citations
15.
Ölmez, Tamer, Zümray Dokur, & E. Yazgan. (2002). Classification of ECG waveforms by using genetic algorithms. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 1. 92–94. 6 indexed citations
16.
Dokur, Zümray, Tamer Ölmez, Mehmet Korürek, & E. Yazgan. (2002). Detection of ECG waveforms by using artificial neural networks. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 3. 929–930. 8 indexed citations
17.
Dokur, Zümray & Tamer Ölmez. (2002). Segmentation of ultrasound images by using a hybrid neural network. Pattern Recognition Letters. 23(14). 1825–1836. 40 indexed citations
18.
Dokur, Zümray. (2002). Segmentation of MR and CT Images Using a Hybrid Neural Network Trained by Genetic Algorithms. Neural Processing Letters. 16(3). 211–225. 5 indexed citations
19.
Dokur, Zümray, et al.. (2002). Compression of the MR and ultrasound images by using wavelet transform. Istanbul Technical University Academic Open Archive (Istanbul Technical University). 3. 1021–1022 vol.2. 1 indexed citations
20.
Dokur, Zümray & Tamer Ölmez. (2001). ECG beat classification by a novel hybrid neural network. Computer Methods and Programs in Biomedicine. 66(2-3). 167–181. 172 indexed citations

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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