69 citations · 98 across the 24 of their papers we have counts for
15 papers · 1 filter
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…
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…
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…
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…
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…
A Dense CNN approach for skin lesion classification
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: Me…