Name
Abstract | ||
|---|---|---|
Cluster ensemble has testified to be a good choice for addressing cluster analysis issues, which is composed of two processes: creating a group of clustering results from a same data set and then combining these results into a final clustering results. How to integrate these results to produce a final one is a significant issue for cluster ensemble. This combination process aims to improve the quality of individual data clustering results. A novel image segmentation algorithm using the Binary k-means and the Adaptive Affinity Propagation clustering (CEBAAP) is designed in this paper. It uses a Binary k-means method to generate a set of clustering results and develops an Adaptive Affinity Propagation clustering to combine these results. The experiments results show that CEBAAP has good image partition effect. |
Year | Venue | Field |
|---|---|---|
2016 | ICYCSEE | Scale-space segmentation,Pattern recognition,Computer science,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Mean-shift,Cluster analysis,Partition (number theory),Minimum spanning tree-based segmentation,Binary number |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Wang | 1 | 0 | 0.68 |
| Guoyin Zhang | 2 | 34 | 11.44 |
| Chen Liu | 3 | 0 | 0.34 |
| Wei Gao | 4 | 26 | 3.61 |