Micaela Verucchi

According to our database, Micaela Verucchi authored at least 16 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds.

Ayoub Raji, Danilo Caporale, Francesco Gatti, Andrea Giove, Micaela Verucchi, Davide Malatesta, Nicola Musiu, Alessandro Toschi, Silviu Roberto Popitanu, Fabio Bagni, Massimiliano Bosi, Alexander Liniger, Marko Bertogna, Daniele Morra, Francesco Amerotti, Luca Bartoli, Federico Martello, Riccardo Porta

Field Robotics, 2024

Guess the Drift with LOP-UKF: LiDAR Odometry and Pacejka Model for Real-Time Racecar Sideslip Estimation.

Alessandro Toschi, Nicola Musiu, Francesco Gatti, Ayoub Raji, Francesco Amerotti, Micaela Verucchi, Marko Bertogna

Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

2023

Model-Based Underwater 6D Pose Estimation From RGB.

Davide Sapienza, Elena Govi, Sara Aldhaheri, Marko Bertogna, Eloy Roura, Èric Pairet, Micaela Verucchi, Paola Ardón

IEEE Robotics Autom. Lett., November, 2023

A survey on real-time DAG scheduling, revisiting the Global-Partitioned Infinity War.

Micaela Verucchi, Ignacio Sañudo Olmedo, Marko Bertogna

Real Time Syst., September, 2023

A benchmark analysis of data-driven and geometric approaches for robot ego-motion estimation.

Marco Legittimo, Simone Felicioni, Fabio Bagni, Andrea Tagliavini, Alberto Dionigi, Francesco Gatti, Micaela Verucchi, Gabriele Costante, Marko Bertogna

J. Field Robotics, May, 2023

Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation.

Elena Govi, Davide Sapienza, Carmelo Scribano, Tobia Poppi, Giorgia Franchini, Paola Ardón, Micaela Verucchi, Marko Bertogna

CoRR, 2023

Model-Based Underwater 6D Pose Estimation from RGB.

Davide Sapienza, Elena Govi, Sara Aldhaheri, Giorgia Franchini, Marko Bertogna, Eloy Roura, Èric Pairet, Micaela Verucchi, Paola Ardón

CoRR, 2023

2022

A Novel Real-Time Edge-Cloud Big Data Management and Analytics Framework for Smart Cities.

Roberto Cavicchioli, Riccardo Martoglia, Micaela Verucchi

J. Univers. Comput. Sci., 2022

Biomedical Image Classification via Dynamically Early Stopped Artificial Neural Network.

Giorgia Franchini, Micaela Verucchi, Ambra Catozzi, Federica Porta, Marco Prato

Algorithms, 2022

Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds.

Ayoub Raji, Alexander Liniger, Andrea Giove, Alessandro Toschi, Nicola Musiu, Daniele Morra, Micaela Verucchi, Danilo Caporale, Marko Bertogna

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

2021

Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehicles.

Ayoosh Bansal, Jayati Singh, Micaela Verucchi, Marco Caccamo, Lui Sha

Proceedings of the 10th Mediterranean Conference on Embedded Computing, 2021

All You Can Embed: Natural Language Based Vehicle Retrieval With Spatio-Temporal Transformers.

Carmelo Scribano, Davide Sapienza, Giorgia Franchini, Micaela Verucchi, Marko Bertogna

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

Latency-Aware Generation of Single-Rate DAGs from Multi-Rate Task Sets.

Micaela Verucchi, Mirco Theile, Marco Caccamo, Marko Bertogna

Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, 2020

Real-Time clustering and LiDAR-camera fusion on embedded platforms for self-driving cars.

Micaela Verucchi, Luca Bartoli, Fabio Bagni, Francesco Gatti, Paolo Burgio, Marko Bertogna

Proceedings of the Fourth IEEE International Conference on Robotic Computing, 2020

A Systematic Assessment of Embedded Neural Networks for Object Detection.

Micaela Verucchi, Gianluca Brilli, Davide Sapienza, Mattia Verasani, Marco Arena, Francesco Gatti, Alessandro Capotondi, Roberto Cavicchioli, Marko Bertogna, Marco Solieri

Proceedings of the 25th IEEE International Conference on Emerging Technologies and Factory Automation, 2020

2019

Mise en abyme with Artificial Intelligence: How to Predict the Accuracy of NN, Applied to Hyper-parameter Tuning.

Giorgia Franchini, Mathilde Galinier, Micaela Verucchi

Proceedings of the Recent Advances in Big Data and Deep Learning, 2019