المؤلفون: Elhosary, Heba, Zakhari, Michael H., Elgammal, Mohamed A., Kelany, Khaled A. Helal, Ghany, Mohamed A. Abd El, Salama, Khaled N., Mostafa, Hassan

المساهمون: Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Electrical and Computer Engineering Program, Sensors Lab, Department of Electronics, German University in Cairo (GUC), New Cairo, Egypt, Department of Electronics and Communications Engineering, Cairo University, Giza, Egypt

مصطلحات موضوعية: Low power, support vector machine (SVM), sequential minimal optimization (SMO), accelerator IP, feature extraction, classification, FPGA, dynamic partial reconfiguration (DPR), ASIC

وصف الملف: application/pdf

Relation: https://ieeexplore.ieee.org/document/9427493/; https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9427493; Elhosary, H., Zakhari, M. H., Elgammal, M. A., Helal Kelany, K. A., Abd El Ghany, M. A., Salama, K. N., & Mostafa, H. (2021). Hardware Acceleration of High Sensitivity Power-Aware Epileptic Seizure Detection System Using Dynamic Partial Reconfiguration. IEEE Access, 1–1. doi:10.1109/access.2021.3079155; 2-s2.0-85105843347; IEEE Access; 1-1; http://hdl.handle.net/10754/669517

الاتاحة: http://hdl.handle.net/10754/669517
https://doi.org/10.1109/ACCESS.2021.3079155

المؤلفون: Salman, Alaa M., Tulan, Ahmed S., Mohamed, Rana Y., Zakhari, Michael H., Mostafa, Hassan

المساهمون: Zewail City of Science and Technology

المصدر: 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)

الاتاحة: http://dx.doi.org/10.1109/niles50944.2020.9257899
http://xplorestaging.ieee.org/ielx7/9257809/9257872/09257899.pdf?arnumber=9257899

المؤلفون: Mohammed, Haitham S., Hassan, Hagar M., Zakhari, Michael H., Mostafa, Hassan, Mohamad, Ebtesam A.

المصدر: Biomedical Engineering / Biomedizinische Technik ; volume 66, issue 6, page 563-572 ; ISSN 0013-5585 1862-278X

الاتاحة: http://dx.doi.org/10.1515/bmt-2021-0084
https://www.degruyter.com/document/doi/10.1515/bmt-2021-0084/xml
https://www.degruyter.com/document/doi/10.1515/bmt-2021-0084/pdf

المؤلفون: Elhosary, Heba, Zakhari, Michael H., ElGammal, Mohamed A., Elghany, Mohamed Abd, Salama, Khaled N., Mostafa, Hassan

المساهمون: Electrical Engineering Program, Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, Department of Electronics, German University in Cairo (GUC), Egypt, Department of Electronics and Communications Engineering, Cairo University, Egypt

مصطلحات موضوعية: Low power, Support vector machine (SVM), Sequential minimal optimization (SMO), Accelerator IP, Feature extraction, Classification, FPGA, ASIC

Relation: https://ieeexplore.ieee.org/document/8867922/; https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8867922; Elhosary, H., Zakhari, M. H., ElGammal, M. A., Abd Elghany, M., Salama, K., & Mostafa, H. (2019). Low-Power Hardware Implementation of a Support Vector Machine Training and Classification for Neural Seizure Detection. IEEE Transactions on Biomedical Circuits and Systems, 1–1. doi:10.1109/tbcas.2019.2947044; IEEE Transactions on Biomedical Circuits and Systems; http://hdl.handle.net/10754/658642

الاتاحة: http://hdl.handle.net/10754/658642
https://doi.org/10.1109/TBCAS.2019.2947044