Federico Nesti

Orcid: 0000-0003-4338-9573

According to our database1, Federico Nesti authored at least 15 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Towards Railway Domain Adaptation for LiDAR-based 3D Detection: Road-to-Rail and Sim-to-Real via SynDRA-BBox.
CoRR, July, 2025

SimPRIVE: a Simulation framework for Physical Robot Interaction with Virtual Environments.
CoRR, April, 2025

Feelbert: A Feedback Linearization-based Embedded Real-Time Quadrupedal Locomotion Framework.
CoRR, April, 2025

SynDRA: Synthetic Dataset for Railway Applications.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

Integrating the Simplex Architecture to Enhance Safety in Deep Learning Autonomous Systems.
Proceedings of the ACM/IEEE 16th International Conference on Cyber-Physical Systems, 2025

2024
On the Real-World Adversarial Robustness of Real-Time Semantic Segmentation Models for Autonomous Driving.
IEEE Trans. Neural Networks Learn. Syst., December, 2024

CARLA-GeAR: A Dataset Generator for a Systematic Evaluation of Adversarial Robustness of Deep Learning Vision Models.
IEEE Trans. Intell. Transp. Syst., August, 2024

2023
TrainSim: A Railway Simulation Framework for LiDAR and Camera Dataset Generation.
IEEE Trans. Intell. Transp. Syst., December, 2023

Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting.
IEEE Trans. Neural Networks Learn. Syst., March, 2023

Defending from Physically-Realizable Adversarial Attacks through Internal Over-Activation Analysis.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
CARLA-GeAR: a Dataset Generator for a Systematic Evaluation of Adversarial Robustness of Vision Models.
CoRR, 2022

Evaluating the Robustness of Semantic Segmentation for Autonomous Driving against Real-World Adversarial Patch Attacks.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

2021
X-BaD: A Flexible Tool for Explanation-Based Bias Detection.
Proceedings of the IEEE International Conference on Cyber Security and Resilience, 2021

2020
A Safe, Secure, and Predictable Software Architecture for Deep Learning in Safety-Critical Systems.
IEEE Embed. Syst. Lett., 2020

2017


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