38 citations · 73 across the 10 of their papers we have counts for
6 papers · 1 filter
Multi-Content Time-Series Popularity Prediction with Multiple-Model Transformers in MEC Networks
Zohreh HajiAkhondi-Meybodi, Arash Mohammadi, Ming Hou +4
Coded/uncoded content placement in Mobile Edge Caching (MEC) has evolved as an efficient solution to meet the significant growth of global mobile data traffic by boosting the conte…
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…
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 (…
FS-HGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography
Elahe Rahimian, Soheil Zabihi, Amir Asif +3
This work is motivated by the recent advances in Deep Neural Networks (DNNs) and their widespread applications in human-machine interfaces. DNNs have been recently used for detecti…
XceptionTime: A Novel Deep Architecture based on Depthwise Separable Convolutions for Hand Gesture Classification
Elahe Rahimian, Soheil Zabihi, Seyed Farokh Atashzar +2
Capitalizing on the need for addressing the existing challenges associated with gesture recognition via sparse multichannel surface Electromyography (sEMG) signals, the paper propo…