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Multilayer Perceptron Development to Identify Plastics Using Fluorescence Lifetime Imaging Microscopy

  • Existing plastic analysis techniques such as Fourier transform infrared spectroscopy and Raman spectroscopy are problematic because samples must be anhydrous and identification can be hindered by additives. This article describes a new approach that has been successfully demonstrated in which plastics can be classified by neural networks that are trained, validated, and tested by frequency domain fluorescence lifetime imaging microscopy measurements.

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Author:Georgekutty Jose Maniyattu, Eldho Geegy, Maximilian Wohlschläger, Nina Leiter, Martin Versen, Christian Laforsch
DOI:https://doi.org/10.31399/asm.edfa.2023-3.p031
Parent Title (English):EDFA Technical Articles
Document Type:Article (peer reviewed)
Language:English
Publication Year:2023
Volume:25
Issue:3
First Page:31
Last Page:37