| Autor: |
Roy, Kuhelee, G, Subhramanya VRK Rao |
| Zdroj: |
2012 5th International Congress on Image & Signal Processing; 1/ 1/2012, p841-846, 6p |
| Abstrakt: |
This paper proposes Adaptive Resonance Theory (ART) based clustering of bag-of-features for image classification. ART is an unsupervised clustering technique. Bag-of-features along with SURF signatures is one of the widely used techniques used in CBIR systems and in other computer vision tasks like classification, recognition etc. KMeans clustering has been one of the traditional techniques used for clustering. Unlike KMeans the number of clusters is not required to be pre-specified in ART based clustering. This advantage of ART has been exploited in this paper for clustering of bag-of-features. [ABSTRACT FROM PUBLISHER] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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