Exploring the Boundaries of On-Device Inference: When Tiny Falls Short, Go Hierarchical

On-device inference holds great potential for increased energy efficiency, responsiveness, and privacy in edge ML systems. However, due to less capable ML models that can be embedded in resource-limited devices, use cases are limited to simple inference tasks such as visual keyword spotting, gesture...

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Veröffentlicht in:	arXiv.org 2024-07
Hauptverfasser:	Adarsh Prasad Behera, Daubaris, Paulius, Bravo, Iñaki, Gallego, José, Morabito, Roberto, Widmer, Joerg, Jaya Prakash Varma Champati
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Edge computing Embedded systems Energy consumption Gesture recognition Hybrid systems Image classification Image contrast Inference Visual tasks
Online-Zugang:	Volltext
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