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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:

Deep Convolutional Neural Networks for Feature-Less Automatic Classification of Independent Components in Multi-Channel Electrophysiological Brain Recordings
Pierpaolo Croce, Filippo Zappasodi, Laura Marzetti, et al.
IEEE Transactions on Biomedical Engineering (2018) Vol. 66, Iss. 8, pp. 2372-2380
Closed Access | Times Cited: 63

Showing 1-25 of 63 citing articles:

Deep Learning in Physiological Signal Data: A Survey
Beanbonyka Rim, Nak-Jun Sung, Se Dong Min, et al.
Sensors (2020) Vol. 20, Iss. 4, pp. 969-969
Open Access | Times Cited: 189
Deep Learning Models for Diagnosis of Schizophrenia Using EEG Signals: Emerging Trends, Challenges, and Prospects
Rakesh Ranjan, Bikash Chandra Sahana, Ashish Kumar Bhandari
Archives of Computational Methods in Engineering (2024) Vol. 31, Iss. 4, pp. 2345-2384
Closed Access | Times Cited: 16
Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review
Chiara Filippini, David Perpetuini, Daniela Cardone, et al.
Applied Sciences (2020) Vol. 10, Iss. 8, pp. 2924-2924
Open Access | Times Cited: 93
Deep Learning in EEG: Advance of the Last Ten-Year Critical Period
Shu Gong, Kaibo Xing, Andrzej Cichocki, et al.
IEEE Transactions on Cognitive and Developmental Systems (2021) Vol. 14, Iss. 2, pp. 348-365
Open Access | Times Cited: 72
Thinker invariance: enabling deep neural networks for BCI across more people
Demetres Kostas, Frank Rudzicz
Journal of Neural Engineering (2020) Vol. 17, Iss. 5, pp. 056008-056008
Open Access | Times Cited: 61
One-dimensional convolutional neural network architecture for classification of mental tasks from electroencephalogram
Manali Saini, Udit Satija, Madhur Deo Upadhayay
Biomedical Signal Processing and Control (2022) Vol. 74, pp. 103494-103494
Open Access | Times Cited: 28
Euthymic bipolar disorder patients and EEG microstates: a neural signature of their abnormal self experience?
Federica Vellante, Francesca Ferri, Gaia Baroni, et al.
Journal of Affective Disorders (2020) Vol. 272, pp. 326-334
Closed Access | Times Cited: 41
Working Memory Decline in Alzheimer’s Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS
David Perpetuini, Antonio Maria Chiarelli, Chiara Filippini, et al.
Entropy (2020) Vol. 22, Iss. 12, pp. 1380-1380
Open Access | Times Cited: 39
CutCat: An augmentation method for EEG classification
Ali Al-Saegh, Shefa A. Dawwd, Jassim M. Abdul-Jabbar
Neural Networks (2021) Vol. 141, pp. 433-443
Closed Access | Times Cited: 38
Deep CNN model based on serial-parallel structure optimization for four-class motor imagery EEG classification
Xuefei Zhao, Dong Liu, Li Ma, et al.
Biomedical Signal Processing and Control (2021) Vol. 72, pp. 103338-103338
Open Access | Times Cited: 32
Transcutaneous Vagus Nerve Stimulation Modulates EEG Microstates and Delta Activity in Healthy Subjects
Lorenzo Ricci, Pierpaolo Croce, Jacopo Lanzone, et al.
Brain Sciences (2020) Vol. 10, Iss. 10, pp. 668-668
Open Access | Times Cited: 36
Mammography Image Quality Assurance Using Deep Learning
Tobias Kretz, Klaus‐Robert Mueller, Tobias Schaeffter, et al.
IEEE Transactions on Biomedical Engineering (2020) Vol. 67, Iss. 12, pp. 3317-3326
Open Access | Times Cited: 34
Evidence of Neurovascular Un-Coupling in Mild Alzheimer’s Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data
Antonio Maria Chiarelli, David Perpetuini, Pierpaolo Croce, et al.
Biomedicines (2021) Vol. 9, Iss. 4, pp. 337-337
Open Access | Times Cited: 31
Automatic Electroencephalogram Artifact Removal Using Deep Convolutional Neural Networks
Fábio Lopes, Adriana Leal, Júlio Medeiros, et al.
IEEE Access (2021) Vol. 9, pp. 149955-149970
Open Access | Times Cited: 31
Machine learning for predicting levetiracetam treatment response in temporal lobe epilepsy
Pierpaolo Croce, Lorenzo Ricci, Patrizia Pulitano, et al.
Clinical Neurophysiology (2021) Vol. 132, Iss. 12, pp. 3035-3042
Closed Access | Times Cited: 28
Data-driven assessment of cardiovascular ageing through multisite photoplethysmography and electrocardiography
Antonio Maria Chiarelli, Francesco Bianco, David Perpetuini, et al.
Medical Engineering & Physics (2019) Vol. 73, pp. 39-50
Closed Access | Times Cited: 31
Fiberless, Multi-Channel fNIRS-EEG System Based on Silicon Photomultipliers: Towards Sensitive and Ecological Mapping of Brain Activity and Neurovascular Coupling
Antonio Maria Chiarelli, David Perpetuini, Pierpaolo Croce, et al.
Sensors (2020) Vol. 20, Iss. 10, pp. 2831-2831
Open Access | Times Cited: 30
Electroencephalography-Derived Prognosis of Functional Recovery in Acute Stroke Through Machine Learning Approaches
Antonio Maria Chiarelli, Pierpaolo Croce, Giovanni Assenza, et al.
International Journal of Neural Systems (2020) Vol. 30, Iss. 12, pp. 2050067-2050067
Closed Access | Times Cited: 30
Adaptation of Convolutional Neural Networks for Multi-Channel Artifact Detection in Chronically Recorded Local Field Potentials
Marcos Fabietti, Mufti Mahmud, Ahmad Lotfi, et al.
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2020)
Closed Access | Times Cited: 28
Deep-MEG: spatiotemporal CNN features and multiband ensemble classification for predicting the early signs of Alzheimer’s disease with magnetoencephalography
Antonio Giovannetti, Gianluca Susi, Paola Casti, et al.
Neural Computing and Applications (2021) Vol. 33, Iss. 21, pp. 14651-14667
Open Access | Times Cited: 24
EEG-Based 3D Visual Fatigue Evaluation Using CNN
Kang Yue, Danli Wang
Electronics (2019) Vol. 8, Iss. 11, pp. 1208-1208
Open Access | Times Cited: 27
DSCNN-CAU: Deep-Learning-Based Mental Activity Classification for IoT Implementation Toward Portable BCI
Manali Saini, Udit Satija, Madhur Deo Upadhayay
IEEE Internet of Things Journal (2022) Vol. 10, Iss. 10, pp. 8944-8957
Closed Access | Times Cited: 14
Optimal deep neural networks by maximization of the approximation power
Hector Calvo-Pardo, Tullio Mancini, José Olmo
Computers & Operations Research (2023) Vol. 156, pp. 106264-106264
Open Access | Times Cited: 7
A systematic review on artifact removal and classification techniques for enhanced MEG-based BCI systems
Beril Susan Philip, Girijesh Prasad, D. Jude Hemanth
Brain-Computer Interfaces (2023) Vol. 10, Iss. 2-4, pp. 99-113
Closed Access | Times Cited: 7
EEG signal-based classification of mental tasks using a one-dimensional ConvResT model
Gunda Manasa, Krashana D. Nirde, Suhas Gajre, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 16, pp. 9053-9072
Closed Access | Times Cited: 2
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