8 citations · 17 across the 10 of their papers we have counts for
6 papers · 1 filter
Accelerating Image-based Pest Detection on a Heterogeneous Multi-core Microcontroller
Luca Bompani, Luca Crupi, Daniele Palossi +5
The codling moth pest poses a significant threat to global crop production, with potential losses of up to 80% in apple orchards. Special camera-based sensor nodes are deployed in…
A Deep Learning-based Pest Insect Monitoring System for Ultra-low Power Pocket-sized Drones
Luca Crupi, Luca Butera, Alberto Ferrante +1
Smart farming and precision agriculture represent game-changer technologies for efficient and sustainable agribusiness. Miniaturized palm-sized drones can act as flexible smart sen…
Fusing Multi-sensor Input with State Information on TinyML Brains for Autonomous Nano-drones
Luca Crupi, Elia Cereda, Daniele Palossi
Autonomous nano-drones (~10 cm in diameter), thanks to their ultra-low power TinyML-based brains, are capable of coping with real-world environments. However, due to their simplifi…
Adaptive Deep Learning for Efficient Visual Pose Estimation aboard Ultra-low-power Nano-drones
Beatrice Alessandra Motetti, Luca Crupi, Mustafa Omer Mohammed Elamin Elshaigi +4
Sub-10cm diameter nano-drones are gaining momentum thanks to their applicability in scenarios prevented to bigger flying drones, such as in narrow environments and close to humans.…
Self-Supervised Learning of Visual Robot Localization Using LED State Prediction as a Pretext Task
Mirko Nava, Nicholas Carlotti, Luca Crupi +2
We propose a novel self-supervised approach for learning to visually localize robots equipped with controllable LEDs. We rely on a few training samples labeled with position ground…
High-throughput Visual Nano-drone to Nano-drone Relative Localization using Onboard Fully Convolutional Networks
Luca Crupi, Alessandro Giusti, Daniele Palossi
Relative drone-to-drone localization is a fundamental building block for any swarm operations. We address this task in the context of miniaturized nano-drones, i.e., 10cm in diamet…