Minimalistic fully convolution networks (MFCN): pixel-level classification for hyperspectral image with few labeled samples.

Most of the existing deep learning methods for hyperspectral image (HSI) classification use pixel-wise or patch-wise classification. In this paper, we propose an image-wise classification method, where the network input is the original hyperspectral cube rather than the spectral curve of each pixel (i.e.