Browse by Relators
Group by: Date | No Grouping
Number of items: 7.
15 December 2023
-
Leonardo Tredese.
Structured Pruning of Vision Transformers at Training Time.
Rel. Daniele Jahier Pagliari, Alessio Burrello, Matteo Risso, Beatrice Alessandra Motetti. Politecnico di Torino, Master of science program in Data Science And Engineering, 2023
13 December 2024
-
Ovidiu Ioan Jitaru.
Human Pose Estimation aboard Nano-drones Using Tiny Vision Transformers.
Rel. Daniele Jahier Pagliari, Beatrice Alessandra Motetti, Alessio Burrello. Politecnico di Torino, Master of science program in Data Science And Engineering, 2024
24 October 2025
-
Carlo Marra.
Slimmable and Early Exit Neural Networks for Object Detection on Nano-Drones.
Rel. Daniele Jahier Pagliari, Alessio Burrello, Beatrice Alessandra Motetti. Politecnico di Torino, Master of science program in Data Science And Engineering, 2025
27 March 2026
-
Francesco Giuseppe Gillio.
Development of a Robotic Framework for the Simulation and Cooperative Navigation of Nano-Drone Swarms.
Rel. Alessio Burrello, Daniele Jahier Pagliari, Giovanni Pollo, Beatrice Alessandra Motetti. Politecnico di Torino, Master of science program in Data Science And Engineering, 2026
24 July 2026
-
Alessandro Valenti.
Active Inference for Autonomous Exploration on Nano-drones.
Rel. Daniele Jahier Pagliari, Alessio Burrello, Beatrice Alessandra Motetti, Matteo Risso, Carlo Marra. Politecnico di Torino, Master of science program in Data Science And Engineering, 2026
-
Redon Karakaci.
Continual Learning Strategies for On-board Gate Detection on Nano-drones.
Rel. Alessio Burrello, Daniele Jahier Pagliari, Beatrice Alessandra Motetti. Politecnico di Torino, Master of science program in Computer Engineering, 2026
-
Pouria Mohammadalipourahari.
Domain Adaptation of Large Language Models for Financial Analysis: A Dual-Adapter Training and Merging Framework.
Rel. Daniele Jahier Pagliari, Beatrice Alessandra Motetti. Politecnico di Torino, Master of science program in Data Science And Engineering, 2026
Up a level