C. Okan Sakar

2.5k citations

41 papers · 1.7k indexed · 2 hit papers · h-index 16

Physiology top 2%
Artificial Intelligence top 2%
Signal Processing top 1%
Neurology top 5%
Computer Vision and Pattern Recognition top 5%

Co-authors: Olcay Kurşun Betül Erdoğdu Şakar Görkem Serbes Hülya Apaydın Fikret Gürgen M. Erdem Isenkul Şakir Delil Ahmet Sertbaş
Topics: Face and Expression Recognition (8 papers)Music and Audio Processing (6 papers)Voice and Speech Disorders (6 papers)
Cited by: Signal Processing Physiology Neurology
Journals: PLoS ONE Expert Systems with Applications Technological Forecasting and Social Change
Partner nations: Türkiye United Kingdom United States

In The Last Decade

C. Okan Sakar

40 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Collection and Analysis of a Parkinson Speech Dataset With Multiple Types of Sound Recordings

2013 464 citations Betül Erdoğdu Şakar, C. Okan Sakar et al. profile →
A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform

2018 352 citations C. Okan Sakar, Görkem Serbes et al. profile →

Peers

Countries citing papers authored by C. Okan Sakar

Since Specialization

Citations

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

Fields of papers citing papers by C. Okan Sakar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. Okan Sakar. 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 C. Okan Sakar. The network helps show where C. Okan Sakar may publish in the future.

Co-authorship network of co-authors of C. Okan Sakar

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Technological forecasting based on estimation of word embedding matrix using LSTM networks 2023 ·Technological Forecasting and Social Change ·(unknown),C. Okan Sakar,Sercan Ozcan	13
2	Deep learning-based Turkish spelling error detection with a multi-class false positive reduction model 2023 ·TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES ·(unknown),C. Okan Sakar	8
3	Creating CREATE queries with multi-task deep neural networks 2023 ·Knowledge-Based Systems ·(unknown),C. Okan Sakar	1
4	Concealed pistol detection from thermal images with deep neural networks 2023 ·Multimedia Tools and Applications ·(unknown),C. Okan Sakar	6
5	Quality of Experience Prediction for VoIP Calls Using Audio MFCCs and Multilayer Perceptron 2022 ·(unknown),H. Hakan Kılınç,C. Okan Sakar	2
6	Stock Market Prediction by Combining Stock Price Information and Sentiment Analysis 2021 ·(unknown),C. Okan Sakar	4
7	Estimation of Parkinson’s disease severity using speech features and extreme gradient boosting 2020 ·Medical & Biological Engineering & Computing ·Hünkar Can Tunç,C. Okan Sakar,Hülya Apaydın,Görkem Serbes,Ayşegül Gündüz,Melih Tütüncü,Fikret Gürgen	36
8	Human Resources Mining for Examination of R&D Progress and Requirements 2020 ·IEEE Transactions on Engineering Management ·Sercan Ozcan,C. Okan Sakar,(unknown)	6
9	Analyzing the effectiveness of vocal features in early telediagnosis of Parkinson's disease 2017 ·PLoS ONE ·Betül Erdoğdu Şakar,Görkem Serbes,C. Okan Sakar	103
10	Determination of the optimal threshold value that can be discriminated by dysphonia measurements for unified Parkinson's Disease rating scale 2015 ·Betül Erdoğdu Şakar,C. Okan Sakar,Görkem Serbes,Olcay Kurşun	7
11	Discriminative Feature Extraction by a Neural Implementation of Canonical Correlation Analysis 2015 ·IEEE Transactions on Neural Networks and Learning Systems ·C. Okan Sakar,Olcay Kurşun	19
12	Combining multiple views: Case studies on protein and arrhythmia features 2013 ·Engineering Applications of Artificial Intelligence ·C. Okan Sakar,Olcay Kurşun,Hüseyin Şeker,Fikret Gürgen,Nizamettin Aydın,Oleg V. Favorov	1
13	Pulmonary crackle detection using time–frequency and time–scale analysis 2012 ·Digital Signal Processing ·Görkem Serbes,C. Okan Sakar,Yasemin P. Kahya,Nizamettin Aydın	67
14	Feature extraction using time-frequency/scale analysis and ensemble of feature sets for crackle detection 2011 ·PubMed ·Görkem Serbes,C. Okan Sakar,Yasemin P. Kahya,Nizamettin Aydın	29
15	A method for combining mutual information and canonical correlation analysis: Predictive Mutual Information and its use in feature selection 2011 ·Expert Systems with Applications ·C. Okan Sakar,Olcay Kurşun	13
16	A feature selection method based on kernel canonical correlation analysis and the minimum Redundancy–Maximum Relevance filter method 2011 ·Expert Systems with Applications ·C. Okan Sakar,Olcay Kurşun,Fikret Gürgen	68
17	Prediction of Protein Sub-nuclear Location by Clustering mRMR Ensemble Feature Selection 2010 ·DMU Open Research Archive (De Montfort University) ·C. Okan Sakar,Olcay Kurşun,Hüseyin Şeker,Fikret Gürgen	3
18	Using covariates for improving the minimum redundancy maximum relevance feature selection method 2010 ·TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES ·Olcay Kurşun,C. Okan Sakar,Oleg V. Favorov,Nizamettin Aydın,(unknown)	17
19	Telediagnosis of Parkinson’s Disease Using Measurements of Dysphonia 2009 ·Journal of Medical Systems ·C. Okan Sakar,Olcay Kurşun	158
20	Prediction and evaluation of tropospheric ozone concentration in Istanbul using artificial neural network modeling according to time parameter 2008 ·Journal of Scientific & Industrial Research ·Göksel Demir,Gökmen Altay,C. Okan Sakar,(unknown),Hüseyin Özdemir,Şenay Yalçın	3

About C. Okan Sakar

C. Okan Sakar is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 41 papers that have together received 1.7k indexed citations. Recurring topics across this work include Face and Expression Recognition (8 papers), Music and Audio Processing (6 papers) and Voice and Speech Disorders (6 papers). The work is most often cited by research in Signal Processing (528 citations), Physiology (808 citations) and Neurology (316 citations). C. Okan Sakar has collaborated with scholars based in Türkiye, United Kingdom and United States. Frequent co-authors include Olcay Kurşun, Betül Erdoğdu Şakar, Görkem Serbes, Hülya Apaydın, Fikret Gürgen, M. Erdem Isenkul, Şakir Delil, Ahmet Sertbaş, Hünkar Can Tunç and Melih Tütüncü. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and Technological Forecasting and Social Change.

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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