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Hierarchical Shrinkage Multi-Scale Network for Hyperspectral Image Classification with Hierarchical Feature Fusion
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Recently, deep learning (DL) based hyperspectral image classification (HSIC) has attracted substantial attention. Many works based on the convolutional neural network (CNN) model have been certificated to be significantly successful for boosting the performance of HSIC. However, most of these methods extract features by using a fixed convolutional kernel and ignore multi-scale features of the ground objects of hyperspectral images (HSIs). Although some recent methods have proposed multi-scale
doi:10.1109/jstars.2021.3083283
fatcat:vgnfuwahxvganblzrjjabmtwc4