A quantized MobileNet on a Raspberry Pi achieves 91.8% sleep/awake and 97.7% crying/normal accuracy on a public neonatal dataset, but the state-of-the-art claim is not supported by direct comparison to prior vision methods.
The Lancet 384(9938), 189–205 (2014)
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Vision-Based Embedded System for Noncontact Monitoring of Preterm Infant Behavior in Low-Resource Care Settings
A quantized MobileNet on a Raspberry Pi achieves 91.8% sleep/awake and 97.7% crying/normal accuracy on a public neonatal dataset, but the state-of-the-art claim is not supported by direct comparison to prior vision methods.