Accountable and uncertainty-aware evaluation of sensor-based AI under distribution shift: devices, subjects, and nearly three years underground
A staged, accountable evaluation protocol that treats the evaluation of a deployed model as a measurement with declared reference levels and a quantified uncertainty and demonstrates the protocol on infrastructure-free geomagnetic localisation with smartphone-based recurrent classifiers in two real underground mines.
Benny Platte, Rico Thomanek, Christian Roschke et al.
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