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Found 13 papers, 1 papers with code
SalFoM: Dynamic Saliency Prediction with Video Foundation Models
Recent advancements in video saliency prediction (VSP) have shown promising performance compared to the human visual system, whose emulation is the primary goal of VSP.
Deep Learning Algorithm for Advanced Level-3 Inverse-Modeling of Silicon-Carbide Power MOSFET Devices
Channel length of power MOSFET is a key parameter involved in the static and dynamic behaviour of the device.
Car-Driver Drowsiness Assessment through 1D Temporal Convolutional Networks
Recently, the scientific progress of Advanced Driver Assistance System solutions (ADAS) has played a key role in enhancing the overall safety of driving.
Visual Saliency Detection in Advanced Driver Assistance Systems
A dedicated 1D temporal deep convolutional network has been devised to classify the collected PPG time-series, enabling us to assess the driver level of attentiveness.
Non-Linear Self Augmentation Deep Pipeline for Cancer Treatment outcome Prediction
Immunotherapy emerges as promising approach for treating cancer.
MeT: A Graph Transformer for Semantic Segmentation of 3D Meshes
Polygonal meshes have become the standard for discretely approximating 3D shapes, thanks to their efficiency and high flexibility in capturing non-uniform shapes.
A baseline on continual learning methods for video action recognition
Continual learning has recently attracted attention from the research community, as it aims to solve long-standing limitations of classic supervisedly-trained models.
Early detection of hip periprosthetic joint infections through CNN on Computed Tomography images
Early detection of an infection prior to prosthesis removal (e. g., hips, knees or other areas) would provide significant benefits to patients.
Deep Learning Systems for Advanced Driving Assistance
This so designed car driver drowsiness monitoring will be combined with further driving safety assessment based on correlated intelligent driving scenario understanding.
UniCT DMI Solution for 3rd COV19D Competition on COVID-19 Detection through attention-based CNN for CT Scan
This paper presents our solution for the first challenge of the 3rd Covid-19 competition, which is part of the "AI-enabled Medical Image Analysis Workshop" organized by IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) 2023.
An Explainable AI System for Automated COVID-19 Assessment and Lesion Categorization from CT-scans
In this work we propose an AI-powered pipeline, based on the deep-learning paradigm, for automated COVID-19 detection and lesion categorization from CT scans.
Hierarchical Domain-Adapted Feature Learning for Video Saliency Prediction
When the base hierarchical model is empowered with domain-specific modules, performance improves, outperforming state-of-the-art models on three out of five metrics on the DHF1K benchmark and reaching the second-best results on the other two.
Domain Adaptation for Outdoor Robot Traversability Estimation from RGB data with Safety-Preserving Loss
Being able to estimate the traversability of the area surrounding a mobile robot is a fundamental task in the design of a navigation algorithm.
