Name
Title | ||
|---|---|---|
A dynamic clustering algorithm based on artificial immune system for analyzing 3D models. |
Abstract | ||
|---|---|---|
In the field of content-based 3D model retrieval, classifying and organizing 3D model database is an important fundamental research, which is critical for improving the retrieval performance. Clustering is one of the most effective methods to classify 3D models. However, there has been little work on it. This paper proposes a dynamic clustering algorithm based on artificial immune system for classifying 3D models, which not only can classify existing models, but can deal with new incremental models. Experimental results show that our algorithm can obtain better classification of 3D models. © 2012 IEEE. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICNC.2012.6234541 | ICNC |
Keywords | Field | DocType |
3d model retrieval,artifiial immune system,clustering,immune response,artificial immune system,classification algorithms,databases,artificial immune systems,immune system,shape,clustering algorithms,computational modeling,solid modeling | Data mining,Canopy clustering algorithm,Artificial immune system,Dynamic clustering,Pattern clustering,Computer science,Solid modelling,Algorithm,Artificial intelligence,Content based retrieval,Cluster analysis,Machine learning | Conference |
Volume | Issue | Citations |
null | null | 0 |
PageRank | References | Authors |
0.34 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinrong Li | 1 | 1266 | 157.76 |
| Chao Gao | 2 | 118 | 19.64 |
| Tianyang Lu | 3 | 1 | 1.04 |
| Li Tao | 4 | 85 | 21.90 |