Clutter rejection by clustering likelihood-based similarities.
Evan HanusaDavid W. KroutMaya R. GuptaPublished in: FUSION (2011)
Keyphrases
- clustering algorithm
- k means
- similarity measure
- clustering method
- similarity matrices
- categorical data
- data clustering
- spectral clustering
- dissimilarity measure
- document clustering
- hierarchical clustering
- em algorithm
- unsupervised learning
- maximum likelihood
- self organizing maps
- nearest neighbor
- fuzzy clustering
- data points
- graph theoretic
- object recognition