activity
20192024
most citedDQLEL: Deep Q-Learning for Energy-Optimized LoS/NLoS UWB Node Selection

48 citations · 164 across the 34 of their papers we have counts for

collaborators

35 papers

eess.IV2024★ 2 cited

Polyp SAM 2: Advancing Zero shot Polyp Segmentation in Colorectal Cancer Detection

Mobina Mansoori, Sajjad Shahabodini, Jamshid Abouei +2

Polyp segmentation plays a crucial role in the early detection and diagnosis of colorectal cancer. However, obtaining accurate segmentations often requires labor-intensive annotati…

cs.LG2024

KnFu: Effective Knowledge Fusion

S. Jamal Seyedmohammadi, S. Kawa Atapour, Jamshid Abouei +1

Federated Learning (FL) has emerged as a prominent alternative to the traditional centralized learning approach. Generally speaking, FL is a decentralized approach that allows for…

eess.IV2024★ 1 cited

HistoSegCap: Capsules for Weakly-Supervised Semantic Segmentation of Histological Tissue Type in Whole Slide Images

Mobina Mansoori, Sajjad Shahabodini, Jamshid Abouei +2

Digital pathology involves converting physical tissue slides into high-resolution Whole Slide Images (WSIs), which pathologists analyze for disease-affected tissues. However, large…

cs.LG2024★ 2 cited

FedD2S: Personalized Data-Free Federated Knowledge Distillation

Kawa Atapour, S. Jamal Seyedmohammadi, Jamshid Abouei +2

This paper addresses the challenge of mitigating data heterogeneity among clients within a Federated Learning (FL) framework. The model-drift issue, arising from the noniid nature…

cs.CV2024

NYCTALE: Neuro-Evidence Transformer for Adaptive and Personalized Lung Nodule Invasiveness Prediction

Sadaf Khademi, Anastasia Oikonomou, Konstantinos N. Plataniotis +1

Drawing inspiration from the primate brain's intriguing evidence accumulation process, and guided by models from cognitive psychology and neuroscience, the paper introduces the NYC…

cs.LG2023

CLSA: Contrastive Learning-based Survival Analysis for Popularity Prediction in MEC Networks

Zohreh Hajiakhondi-Meybodi, Arash Mohammadi, Jamshid Abouei +1

Mobile Edge Caching (MEC) integrated with Deep Neural Networks (DNNs) is an innovative technology with significant potential for the future generation of wireless networks, resulti…

eess.SP2022★ 2 cited

Transformer-based Hand Gesture Recognition via High-Density EMG Signals: From Instantaneous Recognition to Fusion of Motor Unit Spike Trains

Mansooreh Montazerin, Elahe Rahimian, Farnoosh Naderkhani +3

Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In t…

eess.SP2022

HYDRA-HGR: A Hybrid Transformer-based Architecture for Fusion of Macroscopic and Microscopic Neural Drive Information

Mansooreh Montazerin, Elahe Rahimian, Farnoosh Naderkhani +3

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-Ph…

eess.IV2022★ 2 cited

Spatio-Temporal Hybrid Fusion of CAE and SWIn Transformers for Lung Cancer Malignancy Prediction

Sadaf Khademi, Shahin Heidarian, Parnian Afshar +4

The paper proposes a novel hybrid discovery Radiomics framework that simultaneously integrates temporal and spatial features extracted from non-thin chest Computed Tomography (CT)…

cs.LG2022★ 2 cited

ViT-CAT: Parallel Vision Transformers with Cross Attention Fusion for Popularity Prediction in MEC Networks

Zohreh HajiAkhondi-Meybodi, Arash Mohammadi, Ming Hou +2

Mobile Edge Caching (MEC) is a revolutionary technology for the Sixth Generation (6G) of wireless networks with the promise to significantly reduce users' latency via offering stor…

cs.LG2022★ 4 cited

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…

cs.CV2022★ 4 cited

ViT-HGR: Vision Transformer-based Hand Gesture Recognition from High Density Surface EMG Signals

Mansooreh Montazerin, Soheil Zabihi, Elahe Rahimian +2

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 (…

eess.IV2022★ 5 cited

Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark

Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis +22

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 i…

cs.LG2021

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…

cs.LG2021

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…

math.CO2021★ 2 cited

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…

eess.IV2021

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…

cs.LG2021

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…

eess.IV2021★ 2 cited

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…

cs.LG2021

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…

cs.LG2021★ 20 cited

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 (…

eess.IV2021★ 1 cited

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…

cs.NI2021★ 48 cited

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…

eess.IV2021★ 1 cited

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…