Tailorlux supports master thesis on spectral analysis and quantification of optical markers in cotton textiles

Tailorlux has been supporting young scientists for many years. This also applies to a master’s thesis written by Yannik Berndsen on the topic of “Probabilistic Deep Learning for Spectral Analysis and Quantification of Optical Markers in Cotton Textiles”. Tailorlux provided technical and organizational support for the master’s thesis. Yannik was supervised by Tailorlux project engineer Dario Porchetta.

Behind the complex name of the work stands the tedious task of collecting endless cotton samples. Yannik’s goal was to train each available integriTEX sample with an algorithm capable of distinguishing between materials and blends. All of these samples were scanned using the TaQuAs sensor, a quantitative sensor developed by Tailorlux. The master’s thesis also included the development of Tailorlux’s recently issued patent GB2592691.

“The use of deep learning algorithms for spectral analysis in combination with imaging goes far beyond the standards of chemometric models and will allow us to analyze the quantification of ingredients in material streams more accurately than ever before. This step is another milestone in our development roadmap, which we have already secured with our IP rights,” says Dr. Steffen Driever, who also actively supported Yannik during his work at Tailorlux and his master thesis.

The master thesis was handed over to Jun.-Prof. Dr. Risse on March 17, 2022 at the Schlossplatz in Münster.

Tailorlux would like to thank Yannik for his commitment and cooperation and wishes him all the best for his future career.


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