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arXiv Machine Learning By Guillermo Rojas, Gonzalo Soto, Daniel Yunge

Low-Cost Neuromorphic Fall Detection Using Synthetic Event Data and Hybrid SNNs

Read the original on arXiv Machine Learning →

arXiv:2606. 18732v1 Announce Type: new Abstract: This work presents the development of hybrid models that integrate spiking neural networks (SNNs) with components of convolutional neural networks (CNNs) to learn from simulated event-based camera data (Dynamic Vision Sensor, DVS) generated from conventional smartphone videos.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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