Neural network classification of soils with different carbon and calcium content based on hyperspectral data
2023 IX International Conference on Information Technology and Nanotechnology (ITNT)(2023)
摘要
The paper proposes approaches for the classification of high-resolution hyperspectral images in the problem of classification of soil species classification. A spectral-spatial convolutional neural network with compensation for illumination variations is used as a classifier. The effectiveness of the proposed approach in the problem of classification of hyperspectral images of soils obtained by a scanning type hyperspectrometer is shown. A multiclass neural network is compared with an ensemble in which the results of a multiclass neural network are refined by several binary classifiers. It is shown that the use of normalization of illumination inhomogeneity and the use of an ensemble of convolutional spatial-spectral neural networks can significantly increase the accuracy of soil type classification.
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关键词
hyperspectral images,convolutional neural networks,spectral-spatial classification of hyperspectral images
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