The Sky Is Not the Limit. | 0 | 0.34 | 2018 |
The Effect of SOM Size and Similarity Measure on Identification of Functional and Anatomical Regions in fMRI Data. | 0 | 0.34 | 2016 |
An adaptive similarity measure for classification of hyperspectral signatures | 2 | 0.41 | 2013 |
Parallel neural hardware: the time is right. | 1 | 0.35 | 2012 |
gNBXe - a Reconfigurable Neuroprocessor for Various Types of Self-Organizing Maps. | 0 | 0.34 | 2012 |
Unmixing Hyperspectral Images with Fuzzy Supervised Self-Organizing Maps. | 4 | 0.54 | 2012 |
Learning in the context of very high dimensional data (Dagstuhl Seminar 11341). | 3 | 0.41 | 2011 |
Automated Labeling of Materials in Hyperspectral Imagery | 3 | 0.66 | 2010 |
Exploiting data topology in visualization and clustering of self-organizing maps. | 39 | 1.36 | 2009 |
An SOM-Hybrid Supervised Model for the Prediction of Underlying Physical Parameters from Near-Infrared Planetary Spectra | 1 | 0.41 | 2009 |
Learning Highly Structured Manifolds: Harnessing the Power of SOMs | 15 | 0.77 | 2009 |
Machine learning approches and pattern recognition for spectral data | 6 | 0.81 | 2008 |
Cluster Analysis in Remote Sensing Spectral Imagery through Graph Representation and Advanced SOM Visualization | 3 | 0.40 | 2008 |
Advances in computational intelligence and learning | 0 | 0.34 | 2007 |
Data topology visualization for the Self-Organizing Map | 2 | 0.36 | 2006 |
Weighted differential topographic function: a refinement of topographic function | 4 | 0.41 | 2006 |
Forbidden magnification? II. | 0 | 0.34 | 2004 |
Mapping Surface Materials on Mars from Mars Pathfinder Spectral Images with HYPEREYE | 2 | 0.38 | 2004 |
Neural maps in remote sensing image analysis. | 72 | 3.47 | 2003 |
The challenges in spectral image analysis: an introduction, and review of ANN approaches | 6 | 1.01 | 1999 |
Estimating the intrinsic dimensionality of hyperspectral images | 8 | 0.65 | 1999 |
Self-organizing ANNs for planetary surface composition research. | 9 | 1.20 | 1998 |
Hyper-Spectral Satellite Images: Interval Methods May Be Helpful | 0 | 0.34 | 1998 |