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alireza.momenzadeh@uniroma1.it
Alireza Momenzadeh
Dottorando
Struttura:
DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE, ELETTRONICA E TELECOMUNICAZIONI
E-mail:
alireza.momenzadeh@uniroma1.it
Pagina istituzionale corsi di laurea
Curriculum Sapienza
Pubblicazioni
Titolo
Pubblicato in
Anno
Energy-minimizing 3D circular trajectory optimization of rotary-wing UAV under probabilistic path-loss in constrained hotspot environments
VEHICULAR COMMUNICATIONS
2024
Multi-resolution twinned residual auto-encoders (MR-TRAE)—a novel DL model for image multi-resolution
COGNITIVE COMPUTATION
2024
How much BiGAN and CycleGAN-learned hidden features are effective for COVID-19 detection from CT images? A comparative study
THE JOURNAL OF SUPERCOMPUTING
2023
Twinned Residual Auto-Encoder (TRAE)-A new DL architecture for denoising super-resolution and task-aware feature learning from COVID-19 CT images
EXPERT SYSTEMS WITH APPLICATIONS
2023
A novel unsupervised approach based on the hidden features of deep denoising autoencoders for COVID-19 disease detection
EXPERT SYSTEMS WITH APPLICATIONS
2022
Exploiting probability density function of deep convolutional autoencoders’ latent space for reliable COVID-19 detection on CT scans
THE JOURNAL OF SUPERCOMPUTING
2022
AFAFed—Asynchronous Fair Adaptive Federated learning for IoT stream applications
COMPUTER COMMUNICATIONS
2022
Deepfogsim: A toolbox for execution and performance evaluation of the inference phase of conditional deep neural networks with early exits atop distributed fog platforms
APPLIED SCIENCES
2021
An accuracy vs. complexity comparison of deep learning architectures for the detection of covid-19 disease
COMPUTATION
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
IEEE ACCESS
2021
A histogram-based low-complexity approach for the effective detection of COVID-19 disease from CT and X-ray images
APPLIED SCIENCES
2021
Optimized training and scalable implementation of Conditional Deep Neural Networks with early exits for Fog-supported IoT applications
INFORMATION SCIENCES
2020
Metaheuristics and Pontryagin's minimum principle for optimal therapeutic protocols in cancer immunotherapy: a case study and methods comparison
JOURNAL OF MATHEMATICAL BIOLOGY
2020
VirtFogSim: A parallel toolbox for dynamic energy-delay performance testing and optimization of 5G Mobile-Fog-Cloud virtualized platforms
APPLIED SCIENCES
2019
EcoMobiFog–Design and dynamic optimization of a 5G Mobile-Fog-Cloud Multi-Tier ecosystem for the real-time distributed execution of stream applications
IEEE ACCESS
2019
SmartFog: Training the Fog for the energy-saving analytics of Smart-Meter data
APPLIED SCIENCES
2019
On failed methods of fractional differential equations. The case of multi-step generalized differential transform method
MEDITERRANEAN JOURNAL OF MATHEMATICS
2018
Fog-supported delay-constrained energy-saving live migration of VMs over multiPath TCP/IP 5G connections
IEEE ACCESS
2018
Determination of order in linear fractional differential equations
FRACTIONAL CALCULUS & APPLIED ANALYSIS
2018
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