activity
20142025
most citedIntegrating ConvNeXt and Vision Transformers for Enhancing Facial Age Estimation

7 citations · 18 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20257 cited

Integrating ConvNeXt and Vision Transformers for Enhancing Facial Age Estimation

Gaby Maroun, Salah Eddine Bekhouche, Fadi Dornaika

Age estimation from facial images is a complex and multifaceted challenge in computer vision. In this study, we present a novel hybrid architecture that combines ConvNeXt, a state-…

eess.IV20235 cited

D-TrAttUnet: Dual-Decoder Transformer-Based Attention Unet Architecture for Binary and Multi-classes Covid-19 Infection Segmentation

Fares Bougourzi, Cosimo Distante, Fadi Dornaika +1

In the last three years, the world has been facing a global crisis caused by Covid-19 pandemic. Medical imaging has been playing a crucial role in the fighting against this disease…

eess.IV2023

2D and 3D CNN-Based Fusion Approach for COVID-19 Severity Prediction from 3D CT-Scans

Fares Bougourzi, Fadi Dornaika, Amir Nakib +2

Since the appearance of Covid-19 in late 2019, Covid-19 has become an active research topic for the artificial intelligence (AI) community. One of the most interesting AI topics is…

eess.IV20223 cited

Ensemble CNN models for Covid-19 Recognition and Severity Perdition From 3D CT-scan

Fares Bougourzi, Cosimo Distante, Fadi Dornaika +1

Since the appearance of Covid-19 in late 2019, Covid-19 has become an active research topic for the artificial intelligence (AI) community. One of the most interesting AI topics is…

cs.NI20143 cited

Design, Implementation and Simulation of a Cloud Computing System for Enhancing Real-time Video Services by using VANET and Onboard Navigation Systems

Karim Hammoudi, Nabil Ajam, Mohamed Kasraoui +5

In this paper, we propose a design for novel and experimental cloud computing systems. The proposed system aims at enhancing computational, communicational and annalistic capabilit…