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Bassam Moslem
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2010 – 2019
- 2016
- [c12]Mohamad O. Diab, Bassam Moslem, Rami Alkhatib
, Christophe Corbier, Mohamed El Badaoui
Synchrosqueezing Characterize Non-stationary Signals: Application on Gait-Vertical Ground Reaction Force. GSCIT 2016: 66-69 - 2015
- [c11]Rami Alkhatib
Sensors' Ground Reaction Force behavior for both Normal and Parkinson subjects - A qualitative study. EMBC 2015: 4186-4189 - [c10]Bassam Moslem, Ali Mohydeen, Oussama Bazzi:
Monitoring the fetal heart rate variability during labor. EMBC 2015: 5846-5850 - 2013
- [c9]Maher M. Sabbah, Bassam Moslem, Mohamad O. Diab:
Validation of magneto hydrodynamics model. EUSIPCO 2013: 1-5 - 2012
- [j1]Bassam Moslem, Mohamad O. Diab, Mohamad Khalil
Combining data fusion with multiresolution analysis for improving the classification accuracy of uterine EMG signals. EURASIP J. Adv. Signal Process. 2012: 167 (2012) - [c8]Dima Hamdan, Oum-El-Kheir Aktouf, Ioannis Parissis, Bachar El-Hassan, Abbas Hijazi, Bassam Moslem:
A Self-Monitoring, Adaptive and Resource Efficient Approach for Improving QoS in Wireless Sensor Networks. CyberC 2012: 393-400 - [c7]Ramzi Halabi
Cross-correlation analysis of multichannel uterine EMG signals. EMBC 2012: 3106-3109 - [c6]Ramzi Halabi
Detecting missing signals in multichannel recordings by using higher order statistics. EMBC 2012: 3110-3113 - 2011
- [c5]Bassam Moslem, Mohamad O. Diab, Catherine Marque
Classification of multichannel uterine EMG signals. EMBC 2011: 2602-2605 - [c4]Bassam Moslem, Brynjar Karlsson, Mohamad O. Diab, Mohamad Khalil
Classification performance of the frequency-related parameters derived from uterine EMG signals. EMBC 2011: 3371-3374 - [c3]Bassam Moslem, Mohamad Khalil
A multisensor data fusion approach for improving the classification accuracy of uterine EMG signals. ICECS 2011: 93-96 - [c2]Bassam Moslem, Mohamad Khalil
Combining multiple support vector machines for boosting the classification accuracy of uterine EMG signals. ICECS 2011: 631-634 - [c1]Bassam Moslem, Mohamad O. Diab, Mohamad Khalil
Classification of multichannel uterine EMG signals by using unsupervised competitive learning. SiPS 2011: 267-272
Coauthor Index
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