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

Version 1.0.0.0 (8.76 KB) by Nathan Cahill
Performs land-use classification based from multiple-view imaging data
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Updated 25 Mar 2018

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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/

Cite As

Nathan Cahill (2025). Semi-Supervised Normalized Embeddings for Land-Use Classification from Multiple View Data (https://se.mathworks.com/matlabcentral/fileexchange/66630-semi-supervised-normalized-embeddings-for-land-use-classification-from-multiple-view-data), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0.0