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Clustering as physically inspired energy minimization
Huiguang Yang,
Narendra Ahuja
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peer-review
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Keyphrases
Energy Minimization
100%
Energy Terms
100%
Unary
100%
Clustering Methods
75%
Real Image
50%
Energy Model
50%
Synthetic Data
50%
Density-based Spatial Clustering of Applications with Noise (DBSCAN)
50%
Field of Vision
50%
Mean-field Theory
25%
Disjoint
25%
Cutoff Distance
25%
Energy Minimum
25%
Optimization Algorithm
25%
Clustering Algorithm
25%
Energy Optimization
25%
K-means
25%
New View
25%
User Input
25%
Number of Segments
25%
Graph Cuts
25%
Distance Scale
25%
C-means
25%
Clustering Problem
25%
Bandwidth Parameter
25%
Spectral Graph Partitioning
25%
Integer Programming Algorithm
25%
Normalized Cut
25%
Graph Clustering Algorithms
25%
Hierarchical Embedding
25%
Homogeneity Criterion
25%
Smoothness Term
25%
Local Point Density
25%
Energy Optimization Algorithms
25%
Used Energy
25%
Computer Science
Clustering Method
100%
Energy Minimisation
100%
Optimization Algorithm
66%
Synthetic Datasets
66%
Clustering Algorithm
66%
Energy Optimization
66%
Experimental Result
33%
Cutoff Distance
33%
Graph Cut
33%
Integer Programming
33%
Input Parameter
33%
c-mean
33%
Engineering
Energy Minimisation
100%
Energy Term
100%
Real Image
50%
Clustering Algorithm
50%
Experimental Result
25%
Specifies
25%
Input Parameter
25%
Graph Cut
25%
Data Term
25%
Clustering Problem
25%
Scale Distance
25%
Mathematics
Clustering Method
100%
Real Image
66%
Energy Model
66%
Clustering Algorithm
66%
Input Parameter
33%
Integer Programming
33%
Clustering
33%
Density Point
33%