Spectral–Spatial Residual Network for Hyperspectral Image Classification: A 3-D Deep Learning Framework

In this paper, we designed an end-to-end spectral-spatial residual network (SSRN) that takes raw 3-D cubes as input data without feature engineering for hyperspectral image classification. In this network, the spectral and spatial residual blocks consecutively learn discriminative features from abun... View More