Search Results for author:
Found 5 papers, 1 papers with code
Deep Learning Techniques for Hyperspectral Image Analysis in Agriculture: A Review
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.
D-TrAttUnet: Dual-Decoder Transformer-Based Attention Unet Architecture for Binary and Multi-classes Covid-19 Infection Segmentation
The proposed D-TrAttUnet architecture is evaluated for both Binary and Multi-classes Covid-19 infection segmentation.
2D and 3D CNN-Based Fusion Approach for COVID-19 Severity Prediction from 3D CT-Scans
CT-scan imaging is the most informative tool about this disease.
Ensemble CNN models for Covid-19 Recognition and Severity Perdition From 3D CT-scan
On the other hand, we proposed an ensemble of Convolutional Layers with Inception models for Covid-19 severity detection.
A Dense CNN approach for skin lesion classification
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.
