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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Classification of seizure based on the time-frequency image of EEG signals using HHT and SVM
Kai Fu, Jianfeng Qu, Yi Chai, et al.
Biomedical Signal Processing and Control (2014) Vol. 13, pp. 15-22
Closed Access | Times Cited: 230

Showing 1-25 of 230 citing articles:

Classification of epileptic seizures in EEG signals based on phase space representation of intrinsic mode functions
Rajeev Sharma, Ram Bilas Pachori
Expert Systems with Applications (2014) Vol. 42, Iss. 3, pp. 1106-1117
Closed Access | Times Cited: 394
Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals
Rajeev Sharma, Ram Bilas Pachori, U. Rajendra Acharya
Entropy (2015) Vol. 17, Iss. 2, pp. 669-691
Open Access | Times Cited: 297
Automated Diagnosis of Epilepsy Using Key-Point-Based Local Binary Pattern of EEG Signals
Ashwani Kumar Tiwari, Ram Bilas Pachori, Vivek Kanhangad, et al.
IEEE Journal of Biomedical and Health Informatics (2016) Vol. 21, Iss. 4, pp. 888-896
Closed Access | Times Cited: 219
A Multi-View Deep Learning Framework for EEG Seizure Detection
Ye Yuan, Guangxu Xun, Kebin Jia, et al.
IEEE Journal of Biomedical and Health Informatics (2018) Vol. 23, Iss. 1, pp. 83-94
Closed Access | Times Cited: 215
Deep Multi-View Feature Learning for EEG-Based Epileptic Seizure Detection
Xiaobin Tian, Zhaohong Deng, Wenhao Ying, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2019) Vol. 27, Iss. 10, pp. 1962-1972
Open Access | Times Cited: 147
Epileptic seizure identification using entropy of FBSE based EEG rhythms
Vipin Gupta, Ram Bilas Pachori
Biomedical Signal Processing and Control (2019) Vol. 53, pp. 101569-101569
Closed Access | Times Cited: 145
Classification of Contrasting Discrete Emotional States Indicated by EEG Based Graph Theoretical Network Measures
Berke Kılıç, Serap Aydın
Neuroinformatics (2022) Vol. 20, Iss. 4, pp. 863-877
Closed Access | Times Cited: 82
The applied principles of EEG analysis methods in neuroscience and clinical neurology
Hao Zhang, Qing-Qi Zhou, He Chen, et al.
Military Medical Research (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 46
Local pattern transformation based feature extraction techniques for classification of epileptic EEG signals
Abeg Kumar Jaiswal, Haider Banka
Biomedical Signal Processing and Control (2017) Vol. 34, pp. 81-92
Closed Access | Times Cited: 169
Classification of epilepsy EEG signals using DWT-based envelope analysis and neural network ensemble
Mingyang Li, Wanzhong Chen, Tao Zhang
Biomedical Signal Processing and Control (2016) Vol. 31, pp. 357-365
Closed Access | Times Cited: 164
Hilbert marginal spectrum analysis for automatic seizure detection in EEG signals
Kai Fu, Jianfeng Qu, Yi Chai, et al.
Biomedical Signal Processing and Control (2015) Vol. 18, pp. 179-185
Closed Access | Times Cited: 158
Epileptic Seizure Classification of EEGs Using Time–Frequency Analysis Based Multiscale Radial Basis Functions
Yang Li, Xudong Wang, Mei-Lin Luo, et al.
IEEE Journal of Biomedical and Health Informatics (2017) Vol. 22, Iss. 2, pp. 386-397
Closed Access | Times Cited: 148
Epileptic seizure detection in EEG signals using sparse multiscale radial basis function networks and the Fisher vector approach
Yang Li, Wei-Gang Cui, Hui Huang, et al.
Knowledge-Based Systems (2018) Vol. 164, pp. 96-106
Closed Access | Times Cited: 138
Emotion recognition based on EEG features in movie clips with channel selection
Mehmet Siraç Özerdem, Hasan Polat
Brain Informatics (2017) Vol. 4, Iss. 4, pp. 241-252
Open Access | Times Cited: 122
Automatic Seizure Detection using Fully Convolutional Nested LSTM
Yang Li, Zuyi Yu, Yang Chen, et al.
International Journal of Neural Systems (2020) Vol. 30, Iss. 04, pp. 2050019-2050019
Closed Access | Times Cited: 109
A Multi-view Deep Learning Method for Epileptic Seizure Detection using Short-time Fourier Transform
Ye Yuan, Guangxu Xun, Kebin Jia, et al.
(2017), pp. 213-222
Closed Access | Times Cited: 100
A novel approach based on wavelet analysis and arithmetic coding for automated detection and diagnosis of epileptic seizure in EEG signals using machine learning techniques
Hafeez Ullah Amin, Mohd Zuki Yusoff, Rana Fayyaz Ahmad
Biomedical Signal Processing and Control (2019) Vol. 56, pp. 101707-101707
Closed Access | Times Cited: 95
Epileptic Seizure Detection Based on Time-Frequency Images of EEG Signals Using Gaussian Mixture Model and Gray Level Co-Occurrence Matrix Features
Yang Li, Weigang Cui, Mei-Lin Luo, et al.
International Journal of Neural Systems (2018) Vol. 28, Iss. 07, pp. 1850003-1850003
Closed Access | Times Cited: 91
Seizures classification based on higher order statistics and deep neural network
Rahul Sharma, Ram Bilas Pachori, Pradip Sircar
Biomedical Signal Processing and Control (2020) Vol. 59, pp. 101921-101921
Closed Access | Times Cited: 84
One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG
Xiaoshuang Wang, Xiulin Wang, Wenya Liu, et al.
Neurocomputing (2021) Vol. 459, pp. 212-222
Open Access | Times Cited: 84
EEG-Rhythm Specific Taylor–Fourier Filter Bank Implemented With O-Splines for the Detection of Epilepsy Using EEG Signals
José Antonio de la O Serna, Mario R. Arrieta Paternina, A. Zamora, et al.
IEEE Sensors Journal (2020) Vol. 20, Iss. 12, pp. 6542-6551
Closed Access | Times Cited: 71
FFT-based deep feature learning method for EEG classification
Mingyang Li, Wanzhong Chen
Biomedical Signal Processing and Control (2021) Vol. 66, pp. 102492-102492
Closed Access | Times Cited: 66
Classification of sleep apnea based on EEG sub-band signal characteristics
Xiaoyun Zhao, Xiaohong Wang, Tianshun Yang, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 57
Automated detection of epileptic EEGs using a novel fusion feature and extreme learning machine
Jiangling Song, Wenfeng Hu, Rui Zhang
Neurocomputing (2015) Vol. 175, pp. 383-391
Closed Access | Times Cited: 82
Classify epileptic EEG signals using weighted complex networks based community structure detection
Mohammed Diykh, Yan Li, Peng Wen
Expert Systems with Applications (2017) Vol. 90, pp. 87-100
Closed Access | Times Cited: 82
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