Abstract
The determination of multiple parameters via luminescence sensing is of great interest for many applications in different fields, like biosensing and biological imaging, medicine, and diagnostics. The typical approach consists in measuring multiple quantities and in applying complex approximated mathematical models to characterize the sensor response from the relevant parameters. Here a new approach for luminescence sensors is proposed, which allows the determination of multiple physical parameters simultaneously from a single measurement. The new approach is demonstrated by a dual oxygen concentration and temperature sensor. These results are achieved using multi-task deep-learning neural networks.
© 2020 The Author(s)
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