In:
Applied Mechanics and Materials, Trans Tech Publications, Ltd., Vol. 333-335 ( 2013-7), p. 988-991
Abstract:
Image annotation is one of the important technologies in image retrieval and semantic analysis. To overcome the estimation and efficiency problem in CMRM model, we proposed a Visual Concept Distribution based annotation model which estimates the probability through the Visual Concept Set. Experiment results shows that our approach outperforms three classical annotation models (CMRM, CRM and PLSA-WORDS) and closes to the complicated PLSA-FUSION model.
Type of Medium:
Online Resource
ISSN:
1662-7482
DOI:
10.4028/www.scientific.net/AMM.333-335
DOI:
10.4028/www.scientific.net/AMM.333-335.988
Language:
Unknown
Publisher:
Trans Tech Publications, Ltd.
Publication Date:
2013
detail.hit.zdb_id:
2251882-4
