Title :
A long term learning method in CBIR systems by defining semantic templates
Author :
Rashedi, Esmat ; Nezamabadi-pour, Hossein
Author_Institution :
Shahid Bahonar Univ. of Kerman, Kerman, Iran
Abstract :
This paper provides a long term learning method in CBIR systems by defining a kind of semantic template to represent semantic concepts of images. Information, which is achieved in the short learning technique, is used in construction of semantic templates. A similarity function is introduced to find the similarity between queries and semantic templates. The experimental results confirm the effectiveness of the proposed method.
Keywords :
content-based retrieval; image retrieval; learning (artificial intelligence); semantic networks; CBIR systems; content based image retrieval system; long term learning method; queries; semantic templates; short learning technique; similarity function; Equations; Image segmentation; Semantics; Content based image retrieval; Long term learning; Semantic template;
Conference_Titel :
Electrical Engineering (ICEE), 2012 20th Iranian Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4673-1149-6
DOI :
10.1109/IranianCEE.2012.6292549
