Development of a Neural Network for an Automated Differentiation of Plastics using Rapid-FLIM
- 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%.
Author: | Amal Thomas, Shaif Saleem, Nina Leiter, Maximilian Dietlmeier, Maximilian Wohlschläger, Martin Versen, Christian Laforsch |
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DOI: | https://doi.org/10.1364/ES.2023.EW4E.5 |
Parent Title (English): | Optica Sensing Congress 2023 |
Document Type: | Conference Proceeding |
Language: | English |
Publication Year: | 2023 |
Tag: | Fluorescence lifetime imaging; Laser sources; Neural networks; Phase shift; Positron emission tomography; Raman spectroscopy |
Article Number: | EW4E.5 |