The differences in material properties of various common recyclable garbage will be directly mapped to the difference in spectral characteristics. While acquiring the spectral information of the garbage, the hyperspectral imaging technology can obtain the spatial information of the garbage, and realize the rapid detection and classification of garbage by using the method of "spectral-spatial" .The classification model is established combined the spectral characteristics under the sample feature space with CNN (convolutional neural network) machine learning algorithm, and then the classification model is trained and optimized by using database training sample set. Finally, 92.10% classification accuracy is achieved after testing the sample set.
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