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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:

Time-domain exponential energy for epileptic EEG signal classification
O. K. Fasil, R. Rajesh
Neuroscience Letters (2018) Vol. 694, pp. 1-8
Closed Access | Times Cited: 96

Showing 26-50 of 96 citing articles:

Detecting epileptic seizures using machine learning and interpretable features of human EEG
О Э Карпов, Sergey Afinogenov, Vadim Grubov, et al.
The European Physical Journal Special Topics (2022) Vol. 232, Iss. 5, pp. 673-682
Closed Access | Times Cited: 16
Automatic focal EEG identification based on deep reinforcement learning
Xinyu Liu, Xin Ding, Jianping Liu, et al.
Biomedical Signal Processing and Control (2023) Vol. 83, pp. 104693-104693
Closed Access | Times Cited: 10
A Machine Learning Framework for Robust Epileptic Seizure Detection from EEG Sign
Manvendra K. Singh, Gautam Jagyasi, Mohit Garg, et al.
(2023), pp. 1-4
Closed Access | Times Cited: 9
Advanced framework for epilepsy detection through image-based EEG signal analysis
Palani Thanaraj Krishnan, Sudheer Kumar Erramchetty, Bhanu Chander Balusa
Frontiers in Human Neuroscience (2024) Vol. 18
Open Access | Times Cited: 3
Exploring the potential of pretrained CNNs and time-frequency methods for accurate epileptic EEG classification: a comparative study
Mudasir Jamil, Muhammad Zulkifal Aziz, Xiaojun Yu
Biomedical Physics & Engineering Express (2024) Vol. 10, Iss. 4, pp. 045023-045023
Closed Access | Times Cited: 3
Software advancements in automatic epilepsy diagnosis and seizure detection: 10-year review
Palak Handa, Lavanya Lavanya, Nidhi Goel, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 7
Open Access | Times Cited: 3
Improved performance on seizure detection in an automated electroencephalogram signal under evolution by extracting entropy feature
Revathi Munirathinam, P. Suresh, Chinmay Chakraborty, et al.
Multimedia Tools and Applications (2021) Vol. 81, Iss. 10, pp. 13355-13370
Closed Access | Times Cited: 22
An instantaneous frequency and group delay based feature for classifying EEG signals
Nabeel Ali Khan, Sadiq Ali, Kwonhue Choi
Biomedical Signal Processing and Control (2021) Vol. 67, pp. 102562-102562
Closed Access | Times Cited: 21
Epilepsy Detection in EEG Signal using Recurrent Neural Network
Ibrahim Aliyu, Yong Beom Lim, Chang Gyoon Lim
(2019), pp. 50-53
Closed Access | Times Cited: 24
A new stable nonlinear textural feature extraction method based EEG signal classification method using substitution Box of the Hamsi hash function: Hamsi pattern
Türker Tuncer
Applied Acoustics (2020) Vol. 172, pp. 107607-107607
Closed Access | Times Cited: 22
On the Intersection of Signal Processing and Machine Learning: A Use Case-Driven Analysis Approach
Sulaiman Aburakhia, Abdallah Shami, George K. Karagiannidis
(2024)
Open Access | Times Cited: 2
Building EEG-based CAD object selection intention discrimination model using convolutional neural network (CNN)
Beining Cao, Hongwei Niu, Jia Hao, et al.
Advanced Engineering Informatics (2022) Vol. 52, pp. 101548-101548
Closed Access | Times Cited: 12
A review on software and hardware developments in automatic epilepsy diagnosis using EEG datasets
Palak Handa, Esha Gupta, Syed Aneesha Muskan, et al.
Expert Systems (2023) Vol. 40, Iss. 9
Closed Access | Times Cited: 6
Epileptic Activity Detection using Mean Value, RMS, Sample Entropy, and Permutation Entropy Methods
Ceren CANYURT, Reyhan Zengin
The Journal of Cognitive Systems (2023) Vol. 8, Iss. 1, pp. 16-27
Open Access | Times Cited: 6
Epileptic seizure recognition using EEG wavelet decomposition based on nonlinear and statistical features with support vector machine classification
Nabil Dib, R. Benali, F. Bereksi Reguig
Biomedical Engineering / Biomedizinische Technik (2019) Vol. 65, Iss. 2, pp. 133-148
Closed Access | Times Cited: 18
Mental Workload Classification Method Based on EEG Cross-Session Subspace Alignment
Hongquan Qu, Mengyu Zhang, Liping Pang
Mathematics (2022) Vol. 10, Iss. 11, pp. 1875-1875
Open Access | Times Cited: 9
Multi‐kernel‐based random vector functional link network with decomposed features for epileptic EEG signal classification
Sebamai Parija, P.K. Dash, Ranjeeta Bisoi
IET Signal Processing (2020) Vol. 14, Iss. 3, pp. 162-174
Open Access | Times Cited: 13
Efficient Decoding of Affective States from Video-elicited EEG Signals: An Empirical Investigation
Kayhan Latifzadeh, Nima Gozalpour, V. Javier Traver, et al.
ACM Transactions on Multimedia Computing Communications and Applications (2024) Vol. 20, Iss. 10, pp. 1-24
Open Access | Times Cited: 1
Seizure detection using nonlinear measures over EEG frequency bands and deep learning classifiers
Amel Benzaid, Rafik Djemili, Khaled Arbateni
Computer Methods in Biomechanics & Biomedical Engineering (2024), pp. 1-17
Closed Access | Times Cited: 1
Statistical assessment of the inner shape of a channel based on laser speckle contrast imaging
David Abookasis, David Molcho, David Shemesh, et al.
Journal of Modern Optics (2024) Vol. 71, Iss. 7-8, pp. 266-274
Closed Access | Times Cited: 1
An Intelligent Method for Epilepsy Seizure Detection Based on Hybrid Nonlinear EEG Data Features Using Adaptive Signal Decomposition Methods
Sandeep Singh, Harjot Kaur
Circuits Systems and Signal Processing (2022) Vol. 42, Iss. 5, pp. 2782-2803
Closed Access | Times Cited: 7
Epilepsy Detection and Classification for Smart IoT Devices Using hybrid Technique
Sani Saminu, Guizhi Xu, Shuai Zhang, et al.
(2019), pp. 1-6
Closed Access | Times Cited: 10
Hybrid Feature Extraction Technique for Multi-Classification of Ictal and Non-Ictal EEG Epilepsy Signals
Sani Saminu, Guizhi Xu, Shuai Zhang, et al.
ELEKTRIKA- Journal of Electrical Engineering (2020) Vol. 19, Iss. 2, pp. 1-11
Open Access | Times Cited: 10
Empirical Mode Decomposition of EEG Signals for the Effectual Classification of Seizures
O. K. Fasil, R. Rajesh
IntechOpen eBooks (2020)
Open Access | Times Cited: 8
Automated and accurate focal EEG signal detection method based on the cube pattern
Türker Tuncer, Şengül Doğan, M. Çağrı Kaya, et al.
Multimedia Tools and Applications (2023) Vol. 82, Iss. 13, pp. 19675-19691
Closed Access | Times Cited: 3

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