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Title Classification of Textile Samples Using Data Fusion Combining Near- and Mid-Infrared Spectral Information
ID_Doc 23451
Authors Riba, JR; Cantero, R; Puig, R
Title Classification of Textile Samples Using Data Fusion Combining Near- and Mid-Infrared Spectral Information
Year 2022
Published Polymers, 14, 15
DOI 10.3390/polym14153073
Abstract There is an urgent need to reuse and recycle textile fibers, since today, low recycling rates are achieved. Accurate classification methods for post-consumer textile waste are needed in the short term for a higher circularity in the textile and fashion industries. This paper compares different spectroscopic data from textile samples in order to correctly classify the textile samples. The accurate classification of textile waste results in higher recycling rates and a better quality of the recycled materials. The data fusion of near- and mid-infrared spectra is compared with single-spectrum information. The classification results show that data fusion is a better option, providing more accurate classification results, especially for difficult classification problems where the classes are wide and close to one another. The experimental results presented in this paper prove that the data fusion of near- and mid-infrared spectra is a good option for accurate textile-waste classification, since this approach allows the classification results to be significantly improved.
Author Keywords textile waste; classification; data fusion; NIR spectroscopy; FTIR spectroscopy; MIR spectroscopy; circular economy; post-consumer waste
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000839430900001
WoS Category Polymer Science
Research Area Polymer Science
PDF https://www.mdpi.com/2073-4360/14/15/3073/pdf?version=1659094174
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