Aykut Di̇ker

452 total citations
19 papers, 305 citations indexed

About

Aykut Di̇ker is a scholar working on Cardiology and Cardiovascular Medicine, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Aykut Di̇ker has authored 19 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cardiology and Cardiovascular Medicine, 5 papers in Artificial Intelligence and 4 papers in Control and Systems Engineering. Recurrent topics in Aykut Di̇ker's work include ECG Monitoring and Analysis (8 papers), Machine Learning and ELM (5 papers) and EEG and Brain-Computer Interfaces (4 papers). Aykut Di̇ker is often cited by papers focused on ECG Monitoring and Analysis (8 papers), Machine Learning and ELM (5 papers) and EEG and Brain-Computer Interfaces (4 papers). Aykut Di̇ker collaborates with scholars based in Türkiye, India and United States. Aykut Di̇ker's co-authors include Engin Avcı, Zafer Cömert, Derya Avcı, Erkan Tanyıldızı, Mesut Toğaçar, Burhan Ergen, Emrah Dönmez, Serhat Kılıçarslan, Fatih Özyurt and Abdullah Elen and has published in prestigious journals such as Scientia Horticulturae, Measurement and Computers in Biology and Medicine.

In The Last Decade

Aykut Di̇ker

18 papers receiving 291 citations

Peers

Aykut Di̇ker
Hao Dang China
Lang Qin China
Md Shofiqul Islam Bangladesh
M. Ganesan India
Younes Jabrane Morocco
Changchun Liu China
S. Satheeskumaran India
L. V. Rajani Kumari India
Jinlei Liu China
Hao Dang China
Aykut Di̇ker
Citations per year, relative to Aykut Di̇ker Aykut Di̇ker (= 1×) peers Hao Dang

Countries citing papers authored by Aykut Di̇ker

Since Specialization
Citations

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

Fields of papers citing papers by Aykut Di̇ker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aykut Di̇ker

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

All Works

19 of 19 papers shown
1.
Di̇ker, Aykut, et al.. (2024). Identification of multiclass tympanic membranes by using deep feature transfer learning and hyperparameter optimization. Measurement. 229. 114488–114488. 5 indexed citations
2.
Di̇ker, Aykut, et al.. (2024). MI-CSBO: a hybrid system for myocardial infarction classification using deep learning and Bayesian optimization. Computer Methods in Biomechanics & Biomedical Engineering. 29(1). 157–166.
3.
Dönmez, Emrah, et al.. (2024). Multiple deep learning by majority-vote to classify haploid and diploid maize seeds. Scientia Horticulturae. 337. 113549–113549. 1 indexed citations
4.
Dönmez, Emrah, Serhat Kılıçarslan, & Aykut Di̇ker. (2024). Classification of hazelnut varieties based on bigtransfer deep learning model. European Food Research and Technology. 250(5). 1433–1442. 3 indexed citations
5.
Di̇ker, Aykut, et al.. (2024). Trish: an efficient activation function for CNN models and analysis of its effectiveness with optimizers in diagnosing glaucoma. The Journal of Supercomputing. 80(11). 15485–15516. 2 indexed citations
6.
Dönmez, Emrah, et al.. (2023). Identification of haploid and diploid maize seeds using hybrid transformer model. Multimedia Systems. 29(6). 3833–3845. 6 indexed citations
7.
Di̇ker, Aykut, et al.. (2023). An effective feature extraction method for olive peacock eye leaf disease classification. European Food Research and Technology. 250(1). 287–299. 13 indexed citations
8.
Di̇ker, Aykut. (2022). An efficient model of residual based convolutional neural network with Bayesian optimization for the classification of malarial cell images. Computers in Biology and Medicine. 148. 105635–105635. 29 indexed citations
9.
Di̇ker, Aykut. (2021). A Performance Comparison of Pre-trained Deep Learning Models to Classify Brain Tumor. 246–249. 6 indexed citations
10.
Di̇ker, Aykut, et al.. (2021). Examination of the ECG signal classification technique DEA-ELM using deep convolutional neural network features. Multimedia Tools and Applications. 80(16). 24777–24800. 19 indexed citations
11.
Di̇ker, Aykut. (2020). Sıtma Hastalığının Sınıflandırılmasında Evrişimsel Sinir Ağlarının Performanslarının Karşılaştırılması. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 9(4). 1825–1835. 4 indexed citations
12.
Di̇ker, Aykut, et al.. (2019). A novel ECG signal classification method using DEA-ELM. Medical Hypotheses. 136. 109515–109515. 36 indexed citations
13.
Di̇ker, Aykut & Engin Avcı. (2019). Feature Extraction of ECG Signal by using Deep Feature. pp. 1–6. 11 indexed citations
14.
Di̇ker, Aykut, Zafer Cömert, Engin Avcı, Mesut Toğaçar, & Burhan Ergen. (2019). A Novel Application based on Spectrogram and Convolutional Neural Network for ECG Classification. 1–6. 33 indexed citations
15.
Di̇ker, Aykut, et al.. (2018). A new technique for ECG signal classification genetic algorithm Wavelet Kernel extreme learning machine. Optik. 180. 46–55. 53 indexed citations
16.
17.
Di̇ker, Aykut, et al.. (2018). Classification of ECG signal by using machine learning methods. 1–4. 17 indexed citations
18.
Di̇ker, Aykut, et al.. (2017). Determination of R-peaks in ECG signal using Hilbert Transform and Pan-Tompkins Algorithms. 2. 1–4. 12 indexed citations
19.
Di̇ker, Aykut, Zafer Cömert, & Engin Avcı. (2017). A Diagnostic Model for Identification of Myocardial Infarction from Electrocardiography Signals. DergiPark (Istanbul University). 7(2). 132–139. 25 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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