Zobrazeno 1 - 10
of 266
pro vyhledávání: '"Asif, Amir"'
Advancements in Biological Signal Processing (BSP) and Machine-Learning (ML) models have paved the path for development of novel immersive Human-Machine Interfaces (HMI). In this context, there has been a surge of significant interest in Hand Gesture
Externí odkaz:
http://arxiv.org/abs/2210.15119
Deep learning-based Hand Gesture Recognition (HGR) via surface Electromyogram (sEMG) signals has recently shown significant potential for development of advanced myoelectric-controlled prosthesis. Existing deep learning approaches, typically, include
Externí odkaz:
http://arxiv.org/abs/2203.16336
Autor:
Afshar, Parnian, Mohammadi, Arash, Plataniotis, Konstantinos N., Farahani, Keyvan, Kirby, Justin, Oikonomou, Anastasia, Asif, Amir, Wee, Leonard, Dekker, Andre, Wu, Xin, Haque, Mohammad Ariful, Hossain, Shahruk, Hasan, Md. Kamrul, Kamal, Uday, Hsu, Winston, Lin, Jhih-Yuan, Rahman, M. Sohel, Ibtehaz, Nabil, Foisol, Sh. M. Amir, Lam, Kin-Man, Guang, Zhong, Zhang, Runze, Channappayya, Sumohana S., Gupta, Shashank, Dev, Chander
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor. Human-centered segmentation, which is currently the most common approach, is subject to inter-observer var
Externí odkaz:
http://arxiv.org/abs/2201.00458
Recent advancements in Electroencephalography (EEG) sensor technologies and signal processing algorithms have paved the way for further evolution of Brain Computer Interfaces (BCI). When it comes to Signal Processing (SP) for BCI, there has been a su
Externí odkaz:
http://arxiv.org/abs/2201.00283
Autor:
Zabihi, Soheil, Rahimian, Elahe, Marefat, Fatemeh, Asif, Amir, Mohseni, Pedram, Mohammadi, Arash
Objective: The paper focuses on development of robust and accurate processing solutions for continuous and cuff-less blood pressure (BP) monitoring. In this regard, a robust deep learning-based framework is proposed for computation of low latency, co
Externí odkaz:
http://arxiv.org/abs/2112.15271
Autor:
Rahimian, Elahe, Zabihi, Soheil, Asif, Amir, Farina, Dario, Atashzar, S. Farokh, Mohammadi, Arash
Advances in biosignal signal processing and machine learning, in particular Deep Neural Networks (DNNs), have paved the way for the development of innovative Human-Machine Interfaces for decoding the human intent and controlling artificial limbs. DNN
Externí odkaz:
http://arxiv.org/abs/2110.08717
Autor:
Zabihi, Soheil, Rahimian, Elahe, Sharma, Soumya, Sethi, Sean K., Gharabaghi, Sara, Asif, Amir, Haacke, E. Mark, Jog, Mandar S., Mohammadi, Arash
Brain iron deposition, in particular deep gray matter nuclei, increases with advancing age. Hereditary Hemochromatosis (HH) is the most common inherited disorder of systemic iron excess in Europeans and recent studies claimed high brain iron accumula
Externí odkaz:
http://arxiv.org/abs/2110.00203
Autor:
Rahimian, Elahe, Zabihi, Soheil, Asif, Amir, Farina, Dario, Atashzar, S. Farokh, Mohammadi, Arash
There has been a surge of recent interest in Machine Learning (ML), particularly Deep Neural Network (DNN)-based models, to decode muscle activities from surface Electromyography (sEMG) signals for myoelectric control of neurorobotic systems. DNN-bas
Externí odkaz:
http://arxiv.org/abs/2109.12379
Ultrasound elastography is an emerging noninvasive imaging technique wherein pathological alterations can be visualized by revealing the mechanical properties of the tissue. Estimating tissue displacement in all directions is required to accurately e
Externí odkaz:
http://arxiv.org/abs/2012.10562
Publikováno v:
In Energy Conversion and Management 15 February 2024 302
