48 citations · 110 across the 15 of their papers we have counts for
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cs.AR2026
Adaptive AI: Energy Efficient Multi-exit TinyML on Intelligent Vision Systems at the Edge
Luca Crupi, Lorenzo Lamberti, Alessandro Giusti +1
Traditional TinyML systems for edge devices achieve high accuracy by relying on fixed-depth models that require a constant number of multiply-accumulate (MAC) operations regardless…
cs.AR2024
Circuits and Systems for Embodied AI: Exploring uJ Multi-Modal Perception for Nano-UAVs on the Kraken Shield
Viviane Potocnik, Alfio Di Mauro, Lorenzo Lamberti +4
Embodied artificial intelligence (AI) requires pushing complex multi-modal models to the extreme edge for time-constrained tasks such as autonomous navigation of robots and vehicle…