69 citations · 98 across the 24 of their papers we have counts for
25 papers
TMF-RSE: Tri-Modal Fusion with Regional Semantics and Evidential Uncertainty for Lung Severity Scoring
Fadi Abdeladhim Zidi, Salah Eddine Bekhouche, Abdellah Zakaria Sellam +3
Accurate quantification of lung disease severity from chest imaging is critical for clinical decision-making and resource allocation. We propose a tri-modal deep learning framework…
RF-HiT: Rectified Flow Hierarchical Transformer for General Medical Image Segmentation
Ahmed Marouane Djouamaa, Abir Belaala, Abdellah Zakaria Sellam +3
Accurate medical image segmentation requires both long-range contextual reasoning and precise boundary delineation, a task where existing transformer- and diffusion-based paradigms…
When AI and Experts Agree on Error: Intrinsic Ambiguity in Dermatoscopic Images
Loris Cino, Pier Luigi Mazzeo, Alessandro Martella +3
The integration of artificial intelligence (AI), particularly Convolutional Neural Networks (CNNs), into dermatological diagnosis demonstrates substantial clinical potential. While…
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…
VP-Hype: A Hybrid Mamba-Transformer Framework with Visual-Textual Prompting for Hyperspectral Image Classification
Abdellah Zakaria Sellam, Fadi Abdeladhim Zidi, Salah Eddine Bekhouche +4
Accurate classification of hyperspectral imagery (HSI) is often frustrated by the tension between high-dimensional spectral data and the extreme scarcity of labeled training sample…
VLM-PAR: A Vision Language Model for Pedestrian Attribute Recognition
Abdellah Zakaria Sellam, Salah Eddine Bekhouche, Fadi Dornaika +2
Pedestrian Attribute Recognition (PAR) involves predicting fine-grained attributes such as clothing color, gender, and accessories from pedestrian imagery, yet is hindered by sever…
T2IBias: Uncovering Societal Bias Encoded in the Latent Space of Text-to-Image Generative Models
Abu Sufian, Cosimo Distante, Marco Leo +1
Text-to-image (T2I) generative models are largely used in AI-powered real-world applications and value creation. However, their strategic deployment raises critical concerns for re…
C-DiffDet+: Fusing Global Scene Context with Generative Denoising for High-Fidelity Car Damage Detection
Abdellah Zakaria Sellam, Ilyes Benaissa, Salah Eddine Bekhouche +3
Fine-grained object detection in challenging visual domains, such as vehicle damage assessment, presents a formidable challenge even for human experts to resolve reliably. While Di…
CVPD at QIAS 2025 Shared Task: An Efficient Encoder-Based Approach for Islamic Inheritance Reasoning
Salah Eddine Bekhouche, Abdellah Zakaria Sellam, Hichem Telli +2
Islamic inheritance law (Ilm al-Mawarith) requires precise identification of heirs and calculation of shares, which poses a challenge for AI. In this paper, we present a lightweigh…
DemoBias: An Empirical Study to Trace Demographic Biases in Vision Foundation Models
Abu Sufian, Anirudha Ghosh, Debaditya Barman +2
Large Vision Language Models (LVLMs) have demonstrated remarkable capabilities across various downstream tasks, including biometric face recognition (FR) with description. However,…
Beyond Linear Bottlenecks: Spline-Based Knowledge Distillation for Culturally Diverse Art Style Classification
Abdellah Zakaria Sellam, Salah Eddine Bekhouche, Cosimo Distante +1
Art style classification remains a formidable challenge in computational aesthetics due to the scarcity of expertly labeled datasets and the intricate, often nonlinear interplay of…
Markerless Stride Length estimation in Athletic using Pose Estimation with monocular vision
Patryk Skorupski, Cosimo Distante, Pier Luigi Mazzeo
Performance measures such as stride length in athletics and the pace of runners can be estimated using different tricks such as measuring the number of steps divided by the running…
LoLA-SpecViT: Local Attention SwiGLU Vision Transformer with LoRA for Hyperspectral Imaging
Fadi Abdeladhim Zidi, Djamel Eddine Boukhari, Abdellah Zakaria Sellam +4
Hyperspectral image classification remains a challenging task due to the high dimensionality of spectral data, significant inter-band redundancy, and the limited availability of an…
Can Vision Transformers with ResNet's Global Features Fairly Authenticate Demographic Faces?
Abu Sufian, Marco Leo, Cosimo Distante +2
Biometric face authentication is crucial in computer vision, but ensuring fairness and generalization across demographic groups remains a big challenge. Therefore, we investigated…
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…
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…
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…
Forecasting Covid-19 dynamics in Brazil: a data driven approach
Igor G. Pereira, Joris M. Guerin, Andouglas G. Silva Junior +3
This paper has a twofold contribution. The first is a data driven approach for predicting the Covid 19 pandemic dynamics, based on data from more advanced countries. The second is…