George Sakr
George Sakr
St. Joseph University of Beirut (ESIB)
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Cited by
Cited by
Efficient forest fire occurrence prediction for developing countries using two weather parameters
GE Sakr, IH Elhajj, G Mitri
Engineering Applications of Artificial Intelligence 24 (5), 888-894, 2011
Support vector machines to define and detect agitation transition
GE Sakr, IH Elhajj, HAS Huijer
IEEE transactions on affective computing 1 (2), 98-108, 2010
Comparing deep learning and support vector machines for autonomous waste sorting
GE Sakr, M Mokbel, A Darwich, MN Khneisser, A Hadi
2016 IEEE International Multidisciplinary Conference on Engineering …, 2016
Artificial intelligence for forest fire prediction
GE Sakr, IH Elhajj, G Mitri, UC Wejinya
2010 IEEE/ASME international conference on advanced intelligent mechatronics …, 2010
Artificial neural network modeling enhances risk stratification and can reduce downstream testing for patients with suspected acute coronary syndromes, negative cardiac …
HA Isma’eel, PC Cremer, S Khalaf, MM Almedawar, IH Elhajj, GE Sakr, ...
The international journal of cardiovascular imaging 32 (4), 687-696, 2016
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
H Farhat, GE Sakr, R Kilany
Machine vision and applications 31 (6), 1-42, 2020
Multi level SVM for subject independent agitation detection
GE Sakr, IH Elhajj, UC Wejinya
2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2009
Improved accuracy of anticoagulant dose prediction using a pharmacogenetic and artificial neural network-based method
HA Isma’eel, GE Sakr, RH Habib, MM Almedawar, NK Zgheib, IH Elhajj
European journal of clinical pharmacology 70 (3), 265-273, 2014
Subject independent agitation detection
GE Sakr, IH Elhajj, HAS Huijer, C Riley-Doucet, D Debnath
2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics …, 2008
Decision confidence-based multi-level support vector machines
GE Sakr, IH Elhajj
Engineering Applications of Artificial Intelligence 26 (8), 1892-1901, 2013
Artificial intelligence for forest fire prediction: a comparative study
GE Sakr, IHE Hajj, G Mitri
Design and Optimization of a Renewable-Energy Fully-Hybrid Power Supply System in Mobile Radio Access Networks
R Mina, G Sakr
International Journal of Renewable Energy Research (IJRER) 9 (3), 1339-1350, 2019
Digit recognition with confidence
GE Sakr, IH Elhajj
2011 IEEE Workshop on Signal Processing Systems (SiPS), 299-304, 2011
Artificial neural network-based model enhances risk stratification and reduces non-invasive cardiac stress imaging compared to Diamond–Forrester and Morise risk assessment …
HA Isma’eel, GE Sakr, M Serhan, N Lamaa, A Hakim, PC Cremer, ...
Journal of Nuclear Cardiology 25 (5), 1601-1609, 2018
P260 Right cardiac chambers remodeling in marathon and ultra-trail athletes detected by speckle-tracking echocardiography
K Ujka, RM Bruno, B Catuzzo, L Bastiani, A Tonacci, G D'angelo, ...
European Heart Journal-Cardiovascular Imaging 17 (suppl_2), ii45-ii48, 2016
Diamond–Forrester and Morise risk models perform poorly in predicting obstructive coronary disease in Middle Eastern Cohort
HA Isma'eel, M Serhan, GE Sakr, N Lamaa, T Garabedian, I Elhajj, ...
International journal of cardiology 203, 803-805, 2016
VC-based confidence and credibility for support vector machines
GE Sakr, IH Elhajj
Soft Computing 20 (1), 133-147, 2016
A speckle-tracking strain-based artificial neural network model to differentiate cardiomyopathy type
JL Walsh, WA AlJaroudi, N Lamaa, OK Abou Hassan, K Jalkh, IH Elhajj, ...
Scandinavian Cardiovascular Journal 54 (2), 92-99, 2020
Convolution Neural Networks for Arabic Font Recognition
GE Sakr, A Mhanna, R Demerjian
The 15th International Conference on SIGNAL IMAGE TECHNOLOGY & INTERNET …, 2019
Convolution neural network application for road asset detection and classification in lidar point cloud
GE Sakr, L Eido, C Maarawi
Proceedings of SAI Intelligent Systems Conference, 86-100, 2018
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