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pro vyhledávání: '"Montazerin, Mansooreh"'
Neural networks are trained by choosing an architecture and training the parameters. The choice of architecture is often by trial and error or with Neural Architecture Search (NAS) methods. While NAS provides some automation, it often relies on discr
Externí odkaz:
http://arxiv.org/abs/2410.08339
During the COVID-19 pandemic, a major driver of new surges has been the emergence of new variants. When a new variant emerges in one or more countries, other nations monitor its spread in preparation for its potential arrival. The impact of the new v
Externí odkaz:
http://arxiv.org/abs/2401.03390
Autor:
Montazerin, Mansooreh, Rahimian, Elahe, Naderkhani, Farnoosh, Atashzar, S. Farokh, Yanushkevich, Svetlana, Mohammadi, Arash
Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In this context, the paper proposes a compact deep learning framework refe
Externí odkaz:
http://arxiv.org/abs/2212.00743
Autor:
Montazerin, Mansooreh, Rahimian, Elahe, Naderkhani, Farnoosh, Atashzar, S. Farokh, Alinejad-Rokny, Hamid, Mohammadi, Arash
Development of advance surface Electromyogram (sEMG)-based Human-Machine Interface (HMI) systems is of paramount importance to pave the way towards emergence of futuristic Cyber-Physical-Human (CPH) worlds. In this context, the main focus of recent l
Externí odkaz:
http://arxiv.org/abs/2211.02619
Autor:
Montazerin, Mansooreh, Zabihi, Soheil, Rahimian, Elahe, Mohammadi, Arash, Naderkhani, Farnoosh
Recently, there has been a surge of significant interest on application of Deep Learning (DL) models to autonomously perform hand gesture recognition using surface Electromyogram (sEMG) signals. DL models are, however, mainly designed to be applied o
Externí odkaz:
http://arxiv.org/abs/2201.10060
Autor:
Montazerin, Mansooreh, Sajjadifar, Zahra, Pour, Elias Khalili, Riazi-Esfahani, Hamid, Mahmoudi, Tahereh, Rabbani, Hossein, Movahedian, Hossein, Dehghani, Alireza, Akhlaghi, Mohammadreza, Kafieh, Rahele
Given the capacity of Optical Coherence Tomography (OCT) imaging to display symptoms of a wide variety of eye diseases and neurological disorders, the need for OCT image segmentation and the corresponding data interpretation is latterly felt more tha
Externí odkaz:
http://arxiv.org/abs/2003.05916
Autor:
Montazerin, Mansooreh1 (AUTHOR), Rahimian, Elahe2 (AUTHOR), Naderkhani, Farnoosh2 (AUTHOR), Atashzar, S. Farokh3,4 (AUTHOR), Yanushkevich, Svetlana5 (AUTHOR), Mohammadi, Arash1,2 (AUTHOR) arash.mohammadi@concordia.ca
Publikováno v:
Scientific Reports. 7/7/2023, Vol. 13 Issue 1, p1-23. 23p.
Autor:
Montazerin, Mansooreh1, Sajjadifar, Zahra1, Khalili Pour, Elias2, Riazi-Esfahani, Hamid2, Mahmoudi, Tahereh3, Rabbani, Hossein4, Movahedian, Hossein5, Dehghani, Alireza5, Akhlaghi, Mohammadreza5, Kafieh, Rahele4 rkafieh@gmail.com
Publikováno v:
Scientific Reports. 7/2/2021, Vol. 11 Issue 1, p1-13. 13p.
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2022 Jul; Vol. 2022, pp. 5115-5119.