The following publications are possibly variants of this publication:
- Newborn EEG seizure detection using optimized time-frequency matched filterMostefa Mesbah, Mohamed Salah Khlif, Boualem Boashash, Paul B. Colditz. isspa 2007: 1-4 [doi]
- Detection of newborns' EEG seizure using time-frequency divergence measuresPega Zarjam, Ghasem Azemi, Mostefa Mesbah, Boualem Boashash. icassp 2004: 429-432 [doi]
- Seizure detection of newborn EEG using a model based approach: a review of performanceN. Ryan, Mostefa Mesbah, Boualem Boashash. isspa 1999: 243-246 [doi]
- Neonatal eeg seizure detection using a time-frequency matched filter with a reduced template setJohn M. O'Toole, Mostefa Mesbah, Boualem Boashash. isspa 2005: 215-218 [doi]
- Performance evaluation of time-frequency image feature sets for improved classification and analysis of non-stationary signals: Application to newborn EEG seizure detectionBoualem Boashash, Hichem Barki, Samir Ouelha. kbs, 132:188-203, 2017. [doi]
- Alibration of time features and frequency features in the time-frequency domain for improved detection and classification of seizure in newborn EEG signalsYomna Bahnasy, Noha Saad, Larbi Boubchir, Boualem Boashash. isspa 2012: 1442-1443 [doi]
- Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case studyBoualem Boashash, Samir Ouelha. kbs, 106:38-50, 2016. [doi]
- Comparative performance of time-frequency based newborn EEG seizure detection using spike signaturesHamid Hassanpour, Mostefa Mesbah, Boualem Boashash. icassp 2003: 389-392 [doi]
- On the Selection of Time-Frequency Features for Improving the Detection and Classification of Newborn EEG Seizure Signals and Other AbnormalitiesBoualem Boashash, Larbi Boubchir. iconip 2012: 634-643 [doi]