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Development of a Neural Network for an Automated Differentiation of Plastics using Rapid-FLIM

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Abstract

The fast classification and identification of plastics presents a significant challenge. The study assesses the suitability of a Multilayer Perceptron to classify and identify commonly found plastic types using Rapid-FLIM, achieving an accuracy of 88.33%.

© 2023 The Author(s)

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