Fig. 3
From: CEU-Net: ensemble semantic segmentation of hyperspectral images using clustering
Results of our cluster tuning. We explored both K-Means and Gaussian Mixture Models (GMM) for our clustering methods along with a wide spread of cluster numbers. Any cluster larger than 4 for GMM or 6 for K-Means resulted in clusters with too little data for semantic segmentation in specific sub-U-Nets. The number of clusters cannot equal 1, as this would result in the entire dataset being the only cluster and therefore an ensemble CEU-Net approach would not be possible. The relatively small number of clusters in each dataset shows how easily segmentable these datasets are