Semi-supervised learning through hierarchical clustering for interactive aerospace image analysis

Abstract

A new semi-supervised classification algorithm based on the non-parametric clustering algorithm HCA is proposed. The algorithm obtains hierarchical segmentation result where additional classes that are not represented in the training samples can be found. High performance of the algorithm allows using it in interactive mode. Experimental studies confirm that the proposed algorithm provides aerospace image classification in conditions of limited number of training samples.