28 April 2017 Inline hyperspectral thickness determination of thin films using neural networks
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Abstract
Combining reflectometry and hyperspectral imaging allows mapping of thin film thickness. Therefore, layer thickness is calculated by comparing a dataset of simulated spectra with the measured data. Utilizing the maximum frame rate of the hyperspectral imager, the pixel wise spectra comparing procedure cannot be performed using a standard computer due to the processing load. In this work, a method using neural networks for calculating layer thickness is presented. By the use of the nonlinear equation as result of a trained neural network, thickness data can be determined with a measurement rate matching the maximum frame rate of the hyperspectral imager.
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Anton J. Tremmel, Anton J. Tremmel, Roman Weiss, Roman Weiss, Michael Schardt, Michael Schardt, Alexander W. Koch, Alexander W. Koch, } "Inline hyperspectral thickness determination of thin films using neural networks", Proc. SPIE 10213, Hyperspectral Imaging Sensors: Innovative Applications and Sensor Standards 2017, 102130G (28 April 2017); doi: 10.1117/12.2262070; https://doi.org/10.1117/12.2262070
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