Depthwise Separable ResNet in the MAP Framework for Hyperspectral Image Classification
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DOI: 10.1109/lgrs.2020.3033149
Abstract: To build small and efficient neural networks for hyperspectral image (HSI) classification, this letter presents a depthwise separable residual neural network (ResNet). This approach, motivated by the popular MobileNet architecture, decomposes the traditional spatial-spectral convolution… read more here.
Keywords: map framework; depthwise separable; resnet; classification ... See more keywords