1 code implementation • 7 May 2024 • Fares Bougourzi, Fadi Dornaika, Cosimo Distante, Abdelmalik Taleb-Ahmed
Our architecture includes an encoder-decoder structure with a composite Transformer-CNN encoder and dual decoders.
no code implementations • 26 Apr 2023 • Mohamed Fadhlallah Guerri, Cosimo Distante, Paolo Spagnolo, Fares Bougourzi, Abdelmalik Taleb-Ahmed
In the recent years, hyperspectral imaging (HSI) has gained considerably popularity among computer vision researchers for its potential in solving remote sensing problems, especially in agriculture field.
1 code implementation • 27 Mar 2023 • Fares Bougourzi, Cosimo Distante, Fadi Dornaika, Abdelmalik Taleb-Ahmed
The proposed D-TrAttUnet architecture is evaluated for both Binary and Multi-classes Covid-19 infection segmentation.
1 code implementation • 15 Mar 2023 • Fares Bougourzi, Fadi Dornaika, Amir Nakib, Cosimo Distante, Abdelmalik Taleb-Ahmed
CT-scan imaging is the most informative tool about this disease.
no code implementations • 29 Jun 2022 • Fares Bougourzi, Cosimo Distante, Fadi Dornaika, Abdelmalik Taleb-Ahmed
On the other hand, we proposed an ensemble of Convolutional Layers with Inception models for Covid-19 severity detection.
no code implementations • 17 Jul 2018 • Pierluigi Carcagnì, Andrea Cuna, Cosimo Distante
This article presents a Deep CNN, based on the DenseNet architecture jointly with a highly discriminating learning methodology, in order to classify seven kinds of skin lesions: Melanoma, Melanocytic nevus, Basal cell carcinoma, Actinic keratosis / Bowen's disease, Benign keratosis, Dermatofibroma, Vascular lesion.