Alireza Momenzadeh

According to our database, Alireza Momenzadeh authored at least 13 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Multi-resolution Twinned Residual Auto-Encoders (MR-TRAE) - A Novel DL Model for Image Multi-resolution.

Alireza Momenzadeh, Enzo Baccarelli, Michele Scarpiniti, Sima Sarv Ahrabi

Cogn. Comput., July, 2024

Energy-minimizing 3D circular trajectory optimization of rotary-wing UAV under probabilistic path-loss in constrained hotspot environments.

Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh

Veh. Commun., 2024

2023

Twinned Residual Auto-Encoder (TRAE) - A new DL architecture for denoising super-resolution and task-aware feature learning from COVID-19 CT images.

Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh

Expert Syst. Appl., September, 2023

How much BiGAN and CycleGAN-learned hidden features are effective for COVID-19 detection from CT images? A comparative study.

Sima Sarv Ahrabi, Alireza Momenzadeh, Enzo Baccarelli, Michele Scarpiniti, Lorenzo Piazzo

J. Supercomput., 2023

2022

Exploiting probability density function of deep convolutional autoencoders' latent space for reliable COVID-19 detection on CT scans.

Sima Sarv Ahrabi, Lorenzo Piazzo, Alireza Momenzadeh, Michele Scarpiniti, Enzo Baccarelli

J. Supercomput., 2022

A novel unsupervised approach based on the hidden features of Deep Denoising Autoencoders for COVID-19 disease detection.

Michele Scarpiniti, Sima Sarv Ahrabi, Enzo Baccarelli, Lorenzo Piazzo, Alireza Momenzadeh

Expert Syst. Appl., 2022

AFAFed - Protocol analysis.

Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh, Sima Sarv Ahrabi

CoRR, 2022

<i>AFAFed</i> - <i>A</i>synchronous <i>F</i>air <i>A</i>daptive <i>Fed</i>erated learning for IoT stream applications.

Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh, Sima Sarv Ahrabi

Comput. Commun., 2022

2021

An Accuracy vs. Complexity Comparison of Deep Learning Architectures for the Detection of COVID-19 Disease.

Sima Sarv Ahrabi, Michele Scarpiniti, Enzo Baccarelli, Alireza Momenzadeh

Comput., 2021

Learning-in-the-Fog (LiFo): Deep Learning Meets Fog Computing for the Minimum-Energy Distributed Early-Exit of Inference in Delay-Critical IoT Realms.

Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh, Sima Sarv Ahrabi

IEEE Access, 2021

2020

Optimized training and scalable implementation of Conditional Deep Neural Networks with early exits for Fog-supported IoT applications.

Enzo Baccarelli, Simone Scardapane, Michele Scarpiniti, Alireza Momenzadeh, Aurelio Uncini

Inf. Sci., 2020

2019

EcoMobiFog-Design and Dynamic Optimization of a 5G Mobile-Fog-Cloud Multi-Tier Ecosystem for the Real-Time Distributed Execution of Stream Applications.

Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh

IEEE Access, 2019

2018

Fog-Supported Delay-Constrained Energy-Saving Live Migration of VMs Over MultiPath TCP/IP 5G Connections.

Enzo Baccarelli, Michele Scarpiniti, Alireza Momenzadeh

IEEE Access, 2018