Using Neural Networks and NIR Spectrophotometry to Identify Fibers
- 1 August 1994
- journal article
- research article
- Published by SAGE Publications in Textile Research Journal
- Vol. 64 (8) , 444-448
- https://doi.org/10.1177/004051759406400803
Abstract
A qualitative nondestructive technique for fiber identification was developed using near infrared (NIR) spectroscopy. A neural network was trained to identify 17 different fiber types using the NIR absorbance spectra from a library of 390 samples. The neural network model was verified by testing untrained samples. It was not only able to identify single fibers, but was also able to correctly identify blends of fibers from fabrics for which it had not been trained.Keywords
This publication has 9 references indexed in Scilit:
- Improved detection of biological substances using a hybrid neural network and infrared absorption spectroscopyPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Chemometric Data Analysis Using Artificial Neural NetworksApplied Spectroscopy, 1993
- Automatic interpretation of infrared spectra: recognition of aromatic substitution patterns using neural networksJournal of Chemical Information and Computer Sciences, 1992
- Interpretation of infrared spectra by artificial neural networksAnalytica Chimica Acta, 1992
- Neural Network System for the Identification of Infrared SpectraApplied Spectroscopy, 1992
- Comparison of a neural network with multiple linear regression for quantitative analysis in ICP-atomic emission spectroscopyAnalytical and Bioanalytical Chemistry, 1992
- Comparing the performance of neural networks to well-established methods of multivariate data analysis: the classification of mass spectral dataAnalytical and Bioanalytical Chemistry, 1992
- Neural network models for infrared spectrum interpretationMicrochimica Acta, 1991
- A neural network approach to infrared spectrum interpretationMicrochimica Acta, 1990