Browsing by Author "Boubchir L."
Now showing items 1-7 of 7
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Calibration of time features and frequency features in the time-frequency domain for improved detection and classification of seizure in newborn EEG signals
Bahnasy Y.; Saad N.; Boubchir L.; Boashash B. ( IEEE Computer Society , 2012 , Conference Paper)This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by calibrating relevant time features and frequency features in the joint time-frequency domain. The ... -
Classification of EEG signals for detection of epileptic seizure activities based on LBP descriptor of time-frequency images
Boubchir L.; Al-Maadeed, Somaya; Bouridane A.; Cherif A.A. ( IEEE Computer Society , 2015 , Conference Paper)This paper presents novel time-frequency (t-f) feature extraction approach for the classification of EEG signals for Epileptic seizure activities detection. The proposed features are based on Local Binary Patterns (LBP) ... -
Improving the classification of newborn EEG time-frequency representations using a combined time-frequency signal and image approach
Boashash B.; Boubchir L.; Azemi G. (2012 , Conference Paper)This paper presents new time-frequency (T-F) features to improve the classification of non-stationary signals such as EEG signals. Previous methods were based only on signal features that were derived from the instantaneous ... -
On the selection of time-frequency features for improving the detection and classification of newborn EEG seizure signals and other abnormalities
Boashash B.; Boubchir L. (2012 , Conference Paper)This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by translating some relevant time features or frequency features to the joint time-frequency domain. ... -
On the use of time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals
Boubchir L.; Al-Maadeed, Somaya; Bouridane A. ( Institute of Electrical and Electronics Engineers Inc. , 2014 , Conference Paper)This paper proposes new time-frequency features for detecting and classifying epileptic seizure activities in non-stationary EEG signals. These features are obtained by translating and combining the most relevant time-domain ... -
Time-frequency image descriptors-based features for EEG epileptic seizure activities detection and classification
Boubchir L.; Al-Maadeed, Somaya; Bouridane A.; Cherif A.A. ( Institute of Electrical and Electronics Engineers Inc. , 2015 , Conference Paper)This paper presents new class of time-frequency (T-F) features for automatic detection and classification of epileptic seizure activities in EEG signals. Most previous methods were based only on signal features derived ... -
Undecimated wavelet-based Bayesian denoising in mixed Poisson-Gaussian noise with application on medical and biological images
Boubchir L.; Al-Maadeed, Somaya; Bouridane A. ( Institute of Electrical and Electronics Engineers Inc. , 2015 , Conference Paper)Due to photon and readout noise biomedical images are generally contaminated by a mixed Poisson-Gaussian noise. In this paper, we propose a Bayesian image denoising methodology for images corrupted by a mixed Poisson-Gaussian ...