Efficient Recognition and Automatic Sorting Technology of Waste Textiles Based on Online Near infrared Spectroscopy and Convolutional Neural Network

@article{Du2022EfficientRA,
  title={Efficient Recognition and Automatic Sorting Technology of Waste Textiles Based on Online Near infrared Spectroscopy and Convolutional Neural Network},
  author={WenQian Du and Jiahui Zheng and Wenxia Li and Zhenghao Liu and Huaping Wang and Xi Han},
  journal={Resources, Conservation and Recycling},
  year={2022}
}

End-of-Life Textile Recognition in a Circular Economy Perspective: A Methodological Approach Based on Near Infrared Spectroscopy

The life cycle of textiles (i.e., fabrics and apparel products) generates many environmental impacts, such as resource consumption, water, soil, and air pollution through the dispersion of chemical

Classification of Textile Samples Using Data Fusion Combining Near- and Mid-Infrared Spectral Information

TLDR
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.

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