Abstract: Residual Attention Networks (RANs) are a class of Convolutional Neural Networks (CNNs) that integrate attention mechanisms into deep architectures. RANs employ stacked attention modules to ...
Abstract: Very limited training samples pose significant challenges for hyperspectral image (HSI) classification. To address this issue, small-sample learning methods based on classical machine ...
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