02-05-2023 дата публикации
Номер: CN116051886A
Принадлежит:
The invention discloses a hyperspectral image classification method based on an improved Swin-Transform network, and the method comprises the steps: S1, providing a spatial spectrum recombination module for the characteristics of hyperspectral data, and carrying out the preprocessing of the data; and S2, improving a Swin-Transform network, and adding a cross-layer fusion module in the network to avoid information loss in an interlayer feedforward process. By fusing the output of the current layer and the output of the previous layer in the network, the transmission of information from a shallow layer to a deep layer is realized, so that the loss of effective information in a feedforward process is avoided; and S3, inserting a spatial spectrum recombination module into the improved Swin-Transform network, and taking the disclosed hyperspectral image data as training data. The method has the advantages that the accuracy is higher, the efficiency of mining the spectral information by the network ...
Подробнее