JigsawHSI: a network for Hyperspectral Image classification

This article describes the performance of JigsawHSI,a convolutional neural network (CNN) based on Inception but tailored for geoscientific analyses, on classification with the Indian Pines, Pavia University and Salinas hyperspectral image data sets. The network is compared against HybridSN, a spectral-spatial 3D-CNN followed by 2D-CNN that achieves state-of-the-art results in the datasets. This short article proves that JigsawHSI is able to meet or exceed HybridSN performance in all three cases. Additionally, the code and toolkit are made available.