| Tools and techniques for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19 detection SH Safiabadi Tali, JJ LeBlanc, Z Sadiq, OD Oyewunmi, C Camargo, ... Clinical microbiology reviews 34 (3), 10.1128/cmr. 00228-20, 2021 | 432 | 2021 |
| Local feature selection for data classification N Armanfard, JP Reilly, M Komeili IEEE transactions on pattern analysis and machine intelligence 38 (6), 1217-1227, 2016 | 106 | 2016 |
| Self-supervised anomaly detection in computer vision and beyond: A survey and outlook H Hojjati, TKK Ho, N Armanfard Neural Networks 172, 106106, 2024 | 73* | 2024 |
| Liveness detection and automatic template updating using fusion of ECG and fingerprint M Komeili, N Armanfard, D Hatzinakos IEEE Transactions on Information Forensics and Security 13 (7), 1810-1822, 2018 | 73 | 2018 |
| Feature selection for nonstationary data: Application to human recognition using medical biometrics M Komeili, W Louis, N Armanfard, D Hatzinakos IEEE transactions on cybernetics 48 (5), 1446-1459, 2018 | 51 | 2018 |
| Self-supervised acoustic anomaly detection via contrastive learning H Hojjati, N Armanfard ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 50 | 2022 |
| Dasvdd: Deep autoencoding support vector data descriptor for anomaly detection H Hojjati, N Armanfard IEEE Transactions on Knowledge and Data Engineering, 2023 | 47 | 2023 |
| Self-supervised learning for anomalous channel detection in EEG graphs: Application to seizure analysis TKK Ho, N Armanfard Proceedings of the AAAI conference on artificial intelligence 37 (7), 7866-7874, 2023 | 43 | 2023 |
| TED: A texture-edge descriptor for pedestrian detection in video sequences N Armanfard, M Komeili, E Kabir Pattern recognition 45 (3), 983-992, 2012 | 37 | 2012 |
| A novel hybrid algorithm for binarization of badly illuminated document images M Valizadeh, N Armanfard, M Komeili, E Kabir 2009 14th International CSI Computer Conference, 121-126, 2009 | 35 | 2009 |
| A Machine Learning Framework for Automatic and Continuous MMN Detection with Preliminary Results for Coma Outcome Prediction N Armanfard, M Komeili, JP Reilly, J Connoly IEEE journal of biomedical and health informatics, 2019 | 29 | 2019 |
| Vigilance lapse identification using sparse EEG electrode arrays N Armanfard, M Komeili, JP Reilly, L Pino 2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE …, 2016 | 27 | 2016 |
| Multiview Feature Selection for Single-view Classification M Komeili, N Armanfard, D Hatzinakos IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 | 26 | 2020 |
| C3: Cross-instance guided contrastive clustering M Sadeghi, H Hojjati, N Armanfard The 34th British Machine Vision Conference (BMVC 2023), 2022 | 23 | 2022 |
| Logistic Localized Modeling of the Sample Space for Feature Selection and Classification N Armanfard, J Reilly, M Komeili IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109 …, 2018 | 23 | 2018 |
| Multistep networks for roll force prediction in hot strip rolling mill S Shen, D Guye, X Ma, S Yue, N Armanfard Machine Learning with Applications 7, 100245, 2022 | 20 | 2022 |
| Spatio-temporal hard attention learning for skeleton-based activity recognition B Nikpour, N Armanfard Pattern Recognition 139, 109428, 2023 | 19 | 2023 |
| Degraded document image binarization based on combination of two complementary algorithms M Valizadeh, M Komeili, N Armanfard, E Kabir 2009 International Conference on Advances in Computational Tools for …, 2009 | 18 | 2009 |
| On evaluating human recognition using electrocardiogram signals: From rest to exercise M Komeili, W Louis, N Armanfard, D Hatzinakos 2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE …, 2016 | 16 | 2016 |
| Graph-based Time-Series Anomaly Detection: A Survey and Outlook T Kieu Khanh Ho, A Karami, N Armanfard arXiv e-prints, arXiv: 2302.00058, 2023 | 15* | 2023 |
