Landcover classification is an important application in remote sensing, but it always a challenge to distinguish different features with similar characteristics or large-scale differences. Some deep learning networks, such as UperNet, PSPNet, and DANet, use pyramid pooling attention mechanisms improve their abilities multi-scale extraction. However, due the neglect of low-level contained underl...

The fusion of spectral–spatial features based on deep learning has become the focus research in hyperspectral image (HSI) classification. However, previous frameworks usually performed feature aggregation only at branch ends. Furthermore, first-order statistical are considered process, which is not conducive to improving discrimination features. This article proposes a global–local hierarchical...