Semi-Supervised Normalized Embeddings for Land-Use Classification from Multiple View Data

Performs land-use classification based from multiple-view imaging data

Provides example code for performing land-use classification experiments based on the different scenarios described in the paper:
P. G. Immel and N. D. Cahill, "Semi-Supervised Normalized Embeddings for Land-Use Classification from Multiple View Data," Proc. SPIE Defense & Commercial Sensing: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, April 2018.

The provided code runs on the Berlin city data that is available from the 2017 IEEE GRSS Data Fusion Contest, available here: http://www.grss-ieee.org/2017-ieee-grss-data-fusion-contest/