DocumentCode :
2768026
Title :
Self-Organizing Map with Refractoriness and Its Application to Image Retrieval
Author :
Mogami, Hikaru ; Otake, Masahiko ; Kouno, Naoki ; Osana, Yuko
Author_Institution :
Tokyo Univ. of Technol., Tokyo
fYear :
0
fDate :
0-0 0
Firstpage :
1001
Lastpage :
1006
Abstract :
In this research, we propose a self-organizing map with refractoriness (SOMR) and apply it to a similarity-based image retrieval. The proposed SOMR is based on the self-organizing map (SOM) and the refractoriness which is observed in the real neuron is introduced. In the proposed SOMR, the plural neurons in the Map Layer corresponding to the input can fire sequentially because of the refractoriness. The image retrieval system using the SOMR makes use of this property in order to retrieve plural similar images. In this image retrieval system, as the image feature, not only color information but also impression words and key words are employed. We carried out a series of computer experiments and confirmed that the effectiveness of the proposed SOMR and the image retrieval system using the SOMR.
Keywords :
image retrieval; self-organising feature maps; color information; image feature; impression words; key words; map layer; plural neurons; self-organizing map with refractoriness; similarity-based image retrieval; Artificial neural networks; Associative memory; Biological neural networks; Chaos; Character generation; Fires; Image retrieval; Information processing; Information retrieval; Neurons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.246795
Filename :
1716206
Link To Document :
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