Institute of Intelligent Manufacturing, Guangdong Academy of Sciences

Chang Li

Li Qiu

Xingchi Chen

Weixin Liu

Wei Han

Kejia Huang

Yisen Liu

Zefan Qiu

Songbin Zhou

Lawn mower

Disclosed is a hyperspectral data analysis method based on a semi-supervised learning strategy, which includes: hyperspectral sample data is acquired; a sample training set and a prediction set are constructed, herein an unlabeled prediction set sample is used; a regression network based on a generative adversarial network is constructed, including a generator network that generates a sample, and a discriminator/regressor network that has functions of judging the authenticity of the sample and outputting a quantitative analysis value at the same time; a loss function of the generative adversarial network is constructed, including a loss function of the discriminator, a loss function of the regressor, and a loss function of the generator with a sample distribution matching function. The generative adversarial network is used to generate a sample. A sample distribution matching strategy is used to supplement an existing unlabeled sample set. So, the accuracy of hyperspectral quantitative analysis is improved.

Semi-supervised hyperspectral data quantitative analysis method based on generative adversarial network

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Guangdong, China

Chang Li