48 citations · 164 across the 34 of their papers we have counts for
12 papers · 1 filter
BP-Net: Cuff-less, Calibration-free, and Non-invasive Blood Pressure Estimation via a Generic Deep Convolutional Architecture
Soheil Zabihi, Elahe Rahimian, Fatemeh Marefat +3
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 l…
Multi-Agent Reinforcement Learning via Adaptive Kalman Temporal Difference and Successor Representation
Mohammad Salimibeni, Arash Mohammadi, Parvin Malekzadeh +1
Distributed Multi-Agent Reinforcement Learning (MARL) algorithms has attracted a surge of interest lately mainly due to the recent advancements of Deep Neural Networks (DNNs). Conv…
Recolouring planar graphs of girth at least five
Valentin Bartier, Nicolas Bousquet, Carl Feghali +3
For a positive integer , the -recolouring graph of a graph has as vertex set all proper -colourings of with two -colourings being adjacent if they differ by the…
Data Shapley Value for Handling Noisy Labels: An application in Screening COVID-19 Pneumonia from Chest CT Scans
Nastaran Enshaei, Moezedin Javad Rafiee, Arash Mohammadi +1
A long-standing challenge of deep learning models involves how to handle noisy labels, especially in applications where human lives are at stake. Adoption of the data Shapley Value…
Hand Gesture Recognition Using Temporal Convolutions and Attention Mechanism
Elahe Rahimian, Soheil Zabihi, Amir Asif +3
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 Interfac…
CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans
Shahin Heidarian, Parnian Afshar, Anastasia Oikonomou +2
Lung cancer is the leading cause of mortality from cancer worldwide and has various histologic types, among which Lung Adenocarcinoma (LUAC) has recently been the most prevalent on…
Q-Net: A Quantitative Susceptibility Mapping-based Deep Neural Network for Differential Diagnosis of Brain Iron Deposition in Hemochromatosis
Soheil Zabihi, Elahe Rahimian, Soumya Sharma +6
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 e…
TEMGNet: Deep Transformer-based Decoding of Upperlimb sEMG for Hand Gestures Recognition
Elahe Rahimian, Soheil Zabihi, Amir Asif +3
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 (…
Robust Framework for COVID-19 Identification from a Multicenter Dataset of Chest CT Scans
Sadaf Khademi, Shahin Heidarian, Parnian Afshar +8
The objective of this study is to develop a robust deep learning-based framework to distinguish COVID-19, Community-Acquired Pneumonia (CAP), and Normal cases based on chest CT sca…
DQLEL: Deep Q-Learning for Energy-Optimized LoS/NLoS UWB Node Selection
Zohreh Hajiakhondi-Meybodi, Arash Mohammadi, Ming Hou +1
Recent advancements in Internet of Things (IoTs) have brought about a surge of interest in indoor positioning for the purpose of providing reliable, accurate, and energy-efficient…
COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans
Nastaran Enshaei, Anastasia Oikonomou, Moezedin Javad Rafiee +5
Novel Coronavirus disease (COVID-19) is a highly contagious respiratory infection that has had devastating effects on the world. Recently, new COVID-19 variants are emerging making…
Joint Transmission Scheme and Coded Content Placement in Cluster-centric UAV-aided Cellular Networks
Zohreh HajiAkhondi-Meybodi, Arash Mohammadi, Jamshid Abouei +2
Recently, as a consequence of the COVID-19 pandemic, dependence on telecommunication for remote working and telemedicine has significantly increased. In cellular networks, incorpor…