5 citations · 16 across the 24 of their papers we have counts for
6 papers · 1 filter
Uncertainty Aware-Predictive Control Barrier Functions: Safer Human Robot Interaction through Probabilistic Motion Forecasting
Lorenzo Busellato, Federico Cunico, Diego Dall'Alba +4
To enable flexible, high-throughput automation in settings where people and robots share workspaces, collaborative robotic cells must reconcile stringent safety guarantees with the…
A Contrastive Learning-Guided Confident Meta-learning for Zero Shot Anomaly Detection
Muhammad Aqeel, Danijel Skocaj, Marco Cristani +1
Industrial and medical anomaly detection faces critical challenges from data scarcity and prohibitive annotation costs, particularly in evolving manufacturing and healthcare settin…
Robust Anomaly Detection in Industrial Environments via Meta-Learning
Muhammad Aqeel, Shakiba Sharifi, Marco Cristani +1
Anomaly detection is fundamental for ensuring quality control and operational efficiency in industrial environments, yet conventional approaches face significant challenges when tr…
Towards Real Unsupervised Anomaly Detection Via Confident Meta-Learning
Muhammad Aqeel, Shakiba Sharifi, Marco Cristani +1
So-called unsupervised anomaly detection is better described as semi-supervised, as it assumes all training data are nominal. This assumption simplifies training but requires manua…
Meta Learning-Driven Iterative Refinement for Robust Anomaly Detection in Industrial Inspection
Muhammad Aqeel, Shakiba Sharifi, Marco Cristani +1
This study investigates the performance of robust anomaly detection models in industrial inspection, focusing particularly on their ability to handle noisy data. We propose to leve…
New Fashion Products Performance Forecasting: A Survey on Evolutions, Models and Emerging Trends
Andrea Avogaro, Luigi Capogrosso, Andrea Toaiari +2
The fast fashion industry's insatiable demand for new styles and rapid production cycles has led to a significant environmental burden. Overproduction, excessive waste, and harmful…