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Published on: March 13, 2017
Research on Online Rapid Sorting Method of Waste Textiles Based on Near-Infrared Spectroscopy and Generative
Jinquan Hu1,2, Huihua Yang1,3, Guoliang Zhao4
1School of Artificial Intelligence, Beijing University of Posts and Telecommunications, 10 Xitucheng Road, Haidian District, Beijing, China.
Abstract:
In this paper, aiming at the application of online rapid sorting of waste textiles, a large number of effective high-content blending data are generated by using generative adversity network to deeply mine the combination relationship of blending spectra, and A BEGAN-RBF-SVM classification model is constructed by compensating the imbalance of negative samples in the data set. Various experiments show that the model can effectively extract the spectrum of pure textile samples. The classification model has high robustness and high speed, reaches the performance of similar products in the world, and has a broad application market.
