Adaptive Deep Learning for Efficient Visual Pose Estimation aboard Ultra-low-power Nano-drones

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. However, their tiny form factor also brings their major drawback: ultra-constrained memory and processors for the onboa...

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Veröffentlicht in:	arXiv.org 2024-02
Hauptverfasser:	Motetti, Beatrice Alessandra, Crupi, Luca, Mustafa Omer Mohammed Elamin Elshaigi, Risso, Matteo, Pagliari, Daniele Jahier, Palossi, Daniele, Burrello, Alessio
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Closed loops Computing costs Deep learning Feedback control Form factors Machine learning Pose estimation Reduction
Online-Zugang:	Volltext
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