Gamma-ray spectrum classification
AssigneeSymetrica Limited
InventorGeorgi Pavlovski
Life of this patent
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Abstract
A gamma-ray spectrum classification apparatus, comprising circuitry configured: to provide a denoising autoencoder to receive gamma-ray spectrum data representing a gamma-ray spectrum of a material to be classified and to determine feature data indicative of one or more features representative of the gamma-ray spectrum data; and to provide a classification neural network to receive the feature data and to classify the material to be classified as one of a plurality of predetermined classifications using the feature data.
Claims11
A gamma-ray spectrum classification apparatus, comprising circuitry configured:
- to provide a denoising autoencoder to receive deconvolved gamma-ray spectrum data representing a gamma-ray spectrum of a material to be classified and to denoise the deconvolved gamma-ray spectrum data to determine feature data indicative of one or more features representative of the gamma-ray spectrum data;
- and
- to provide a classification neural network to receive the feature data and to classify the material to be classified as one of a plurality of predetermined classifications using the feature data.
A gamma-ray spectrum classification method, comprising:
- receiving deconvolved gamma-ray spectrum data representing a gamma-ray spectrum of a material to be classified and denoising the deconvolved gamma-ray spectrum data to determine feature data indicative of one or more features representative of the gamma-ray spectrum data using a denoising autoencoder;
- and
- using the feature data to classify the material to be classified as one of a plurality of predetermined classifications using a classification neural network.
Dependencies are inferred from the claim text.