1 citations · 2 across the 10 of their papers we have counts for
10 papers
Cross-Modal Mapping and Dual-Branch Reconstruction for 2D-3D Multimodal Industrial Anomaly Detection
Radia Daci, Vito Renò, Cosimo Patruno +4
Multimodal industrial anomaly detection benefits from integrating RGB appearance with 3D surface geometry, yet existing \emph{unsupervised} approaches commonly rely on memory banks…
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…
Mamba Adaptive Anomaly Transformer with association discrepancy for time series
Abdellah Zakaria Sellam, Ilyes Benaissa, Abdelmalik Taleb-Ahmed +2
Anomaly detection in time series is essential for industrial monitoring and environmental sensing, yet distinguishing anomalies from complex patterns remains challenging. Existing…
Electrostatic Force Regularization for Neural Structured Pruning
Abdesselam Ferdi, Abdelmalik Taleb-Ahmed, Amir Nakib +1
The demand for deploying deep convolutional neural networks (DCNNs) on resource-constrained devices for real-time applications remains substantial. However, existing state-of-the-a…
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…
Boosting House Price Estimations with Multi-Head Gated Attention
Zakaria Abdellah Sellam, Cosimo Distante, Abdelmalik Taleb-Ahmed +1
Evaluating house prices is crucial for various stakeholders, including homeowners, investors, and policymakers. However, traditional spatial interpolation methods have limitations…
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-…