13 citations · 31 across the 8 of their papers we have counts for
8 papers
Uncertainty-Aware Mapping from 3D Keypoints to Anatomical Landmarks for Markerless Biomechanics
Cesare Davide Pace, Alessandro Marco De Nunzio, Claudio De Stefano +2
Markerless biomechanics increasingly relies on 3D skeletal keypoints extracted from video, yet downstream biomechanical mappings typically treat these estimates as deterministic, p…
Character Detection using YOLO for Writer Identification in multiple Medieval books
Alessandra Scotto di Freca, Tiziana D Alessandro, Francesco Fontanella +2
Paleography is the study of ancient and historical handwriting, its key objectives include the dating of manuscripts and understanding the evolution of writing. Estimating when a d…
When Deep Learning Fails: Limitations of Recurrent Models on Stroke-Based Handwriting for Alzheimer's Disease Detection
Emanuele Nardone, Tiziana D'Alessandro, Francesco Fontanella +1
Alzheimer's disease detection requires expensive neuroimaging or invasive procedures, limiting accessibility. This study explores whether deep learning can enable non-invasive Alzh…
Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imaging
Gabriele Lozupone, Alessandro Bria, Francesco Fontanella +3
This study presents Latent Diffusion Autoencoder (LDAE), a novel encoder-decoder diffusion-based framework for efficient and meaningful unsupervised learning in medical imaging, fo…
Poseidon: A ViT-based Architecture for Multi-Frame Pose Estimation with Adaptive Frame Weighting and Multi-Scale Feature Fusion
Cesare Davide Pace, Alessandro Marco De Nunzio, Claudio De Stefano +2
Human pose estimation, a vital task in computer vision, involves detecting and localising human joints in images and videos. While single-frame pose estimation has seen significant…
AXIAL: Attention-based eXplainability for Interpretable Alzheimer's Localized Diagnosis using 2D CNNs on 3D MRI brain scans
Gabriele Lozupone, Alessandro Bria, Francesco Fontanella +2
This study presents an innovative method for Alzheimer's disease diagnosis using 3D MRI designed to enhance the explainability of model decisions. Our approach adopts a soft attent…
A Machine Learning Approach to Analyze the Effects of Alzheimer's Disease on Handwriting through Lognormal Features
Tiziana D'Alessandro, Cristina Carmona-Duarte, Claudio De Stefano +3
Alzheimer's disease is one of the most incisive illnesses among the neurodegenerative ones, and it causes a progressive decline in cognitive abilities that, in the worst cases, bec…
How word semantics and phonology affect handwriting of Alzheimer's patients: a machine learning based analysis
Nicole Dalia Cilia, Claudio De Stefano, Francesco Fontanella +1
Using kinematic properties of handwriting to support the diagnosis of neurodegenerative disease is a real challenge: non-invasive detection techniques combined with machine learnin…