8 citations · 17 across the 15 of their papers we have counts for
15 papers
Decoding Matters: Efficient Mamba-Based Decoder with Distribution-Aware Deep Supervision for Medical Image Segmentation
Fares Bougourzi, Fadi Dornaika, Abdenour Hadid
Deep learning has achieved remarkable success in medical image segmentation, often reaching expert-level accuracy in delineating tumors and tissues. However, most existing approach…
MambaCAFU: Hybrid Multi-Scale and Multi-Attention Model with Mamba-Based Fusion for Medical Image Segmentation
T-Mai Bui, Fares Bougourzi, Fadi Dornaika +1
In recent years, deep learning has shown near-expert performance in segmenting complex medical tissues and tumors. However, existing models are often task-specific, with performanc…
Lung Infection Severity Prediction Using Transformers with Conditional TransMix Augmentation and Cross-Attention
Bouthaina Slika, Fadi Dornaika, Fares Bougourzi +1
Lung infections, particularly pneumonia, pose serious health risks that can escalate rapidly, especially during pandemics. Accurate AI-based severity prediction from medical imagin…
Recent Advances in Medical Imaging Segmentation: A Survey
Fares Bougourzi, Abdenour Hadid
Medical imaging is a cornerstone of modern healthcare, driving advancements in diagnosis, treatment planning, and patient care. Among its various tasks, segmentation remains one of…
Advancing Wheat Crop Analysis: A Survey of Deep Learning Approaches Using Hyperspectral Imaging
Fadi Abdeladhim Zidi, Abdelkrim Ouafi, Fares Bougourzi +2
As one of the most widely cultivated and consumed crops, wheat is essential to global food security. However, wheat production is increasingly challenged by pests, diseases, climat…
Extremely Fine-Grained Visual Classification over Resembling Glyphs in the Wild
Fares Bougourzi, Fadi Dornaika, Chongsheng Zhang
Text recognition in the wild is an important technique for digital maps and urban scene understanding, in which the natural resembling properties between glyphs is one of the major…
Boosting Hyperspectral Image Classification with Gate-Shift-Fuse Mechanisms in a Novel CNN-Transformer Approach
Mohamed Fadhlallah Guerri, Cosimo Distante, Paolo Spagnolo +2
During the process of classifying Hyperspectral Image (HSI), every pixel sample is categorized under a land-cover type. CNN-based techniques for HSI classification have notably adv…
D-TrAttUnet: Toward Hybrid CNN-Transformer Architecture for Generic and Subtle Segmentation in Medical Images
Fares Bougourzi, Fadi Dornaika, Cosimo Distante +1
Over the past two decades, machine analysis of medical imaging has advanced rapidly, opening up significant potential for several important medical applications. As complicated dis…
Artificial Intelligence in Bone Metastasis Analysis: Current Advancements, Opportunities and Challenges
Marwa Afnouch, Fares Bougourzi, Olfa Gaddour +2
In recent years, Artificial Intelligence (AI) has been widely used in medicine, particularly in the analysis of medical imaging, which has been driven by advances in computer visio…
Rethinking Attention Gated with Hybrid Dual Pyramid Transformer-CNN for Generalized Segmentation in Medical Imaging
Fares Bougourzi, Fadi Dornaika, Abdelmalik Taleb-Ahmed +1
Inspired by the success of Transformers in Computer vision, Transformers have been widely investigated for medical imaging segmentation. However, most of Transformer architecture a…
Ensembling and Test Augmentation for Covid-19 Detection and Covid-19 Domain Adaptation from 3D CT-Scans
Fares Bougourzi, Feryal Windal Moula, Halim Benhabiles +2
Since the emergence of Covid-19 in late 2019, medical image analysis using artificial intelligence (AI) has emerged as a crucial research area, particularly with the utility of CT-…
Deep Learning Techniques for Hyperspectral Image Analysis in Agriculture: A Review
Mohamed Fadhlallah Guerri, Cosimo Distante, Paolo Spagnolo +2
In the recent years, hyperspectral imaging (HSI) has gained considerably popularity among computer vision researchers for its potential in solving remote sensing problems, especial…
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…
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…
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…