Cargando…
Classification of Textile Samples Using Data Fusion Combining Near- and Mid-Infrared Spectral Information
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 spect...
Autores principales: | Riba, Jordi-Roger, Cantero, Rosa, Puig, Rita |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370096/ https://www.ncbi.nlm.nih.gov/pubmed/35956591 http://dx.doi.org/10.3390/polym14153073 |
Ejemplares similares
-
Post-Consumer Textile Waste Classification through Near-Infrared Spectroscopy, Using an Advanced Deep Learning Approach
por: Riba, Jordi-Roger, et al.
Publicado: (2022) -
Mid and Near-Infrared Reflection Spectral Database of Natural Organic Materials in the Cultural Heritage Field
por: Invernizzi, Claudia, et al.
Publicado: (2018) -
Integrated near-infrared spectral sensing
por: Hakkel, Kaylee D., et al.
Publicado: (2022) -
Comparing the effect of different sample conditions and spectral libraries on the prediction accuracy of soil properties from near- and mid-infrared spectra at the field-scale
por: Breure, T.S., et al.
Publicado: (2022) -
Improved Model for Starch Prediction in Potato by the Fusion of Near-Infrared Spectral and Textural Data
por: Wang, Fuxiang, et al.
Publicado: (2022)