From the 1 of 7 linked papers with an AI index.
7 papers
Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehicles
Luca de Martino, Federico Aromolo, Federico Nesti +1
The paper proposes an efficient, real‑time anomaly segmentation pipeline for autonomous vehicles by reformulating PixOOD's Neyman‑Pearson scoring and deploying it with TensorRT, ac…
Integrating Object Detection, LiDAR-Enhanced Depth Estimation, and Segmentation Models for Railway Environments
Enrico Francesco Giannico, Federico Nesti, Gianluca D'Amico +5
Obstacle detection in railway environments is crucial for ensuring safety. However, very few studies address the problem using a complete, modular, and flexible system that can bot…
OSDaR-AR: Enhancing Railway Perception Datasets via Multi-modal Augmented Reality
Federico Nesti, Gianluca D'Amico, Mauro Marinoni +1
Although deep learning has significantly advanced the perception capabilities of intelligent transportation systems, railway applications continue to suffer from a scarcity of high…
The Use of the Simplex Architecture to Enhance Safety in Deep-Learning-Powered Autonomous Systems
Federico Nesti, Niko Salamini, Mauro Marinoni +4
Recently, the outstanding performance reached by neural networks in many tasks has led to their deployment in autonomous systems, such as robots and vehicles. However, neural netwo…
Towards Railway Domain Adaptation for LiDAR-based 3D Detection: Road-to-Rail and Sim-to-Real via SynDRA-BBox
Xavier Diaz, Gianluca D'Amico, Raul Dominguez-Sanchez +3
In recent years, interest in automatic train operations has significantly increased. To enable advanced functionalities, robust vision-based algorithms are essential for perceiving…
SimPRIVE: a Simulation framework for Physical Robot Interaction with Virtual Environments
Federico Nesti, Gianluca D'Amico, Mauro Marinoni +1
The use of machine learning in cyber-physical systems has attracted the interest of both industry and academia. However, no general solution has yet been found against the unpredic…