DocumentCode :
1797387
Title :
Weighted grid Principal Component Analysis hashing
Author :
Xiancheng Zhou ; Zhiqian Huang ; Ng, Wing W. Y.
Volume :
1
fYear :
2014
fDate :
13-16 July 2014
Firstpage :
200
Lastpage :
205
Abstract :
Principal Component Analysis (PCA) is one of the most widely used components of hashing. In this paper, we propose three PCA-based hashing methods to improve the performance of the Principal Component Hashing (PCH). Different principal components have different among of variances of data. In the PCH, each principal component corresponds to a hash function. Hence, the PCH treats each principal component to have the same importance which will lead to the loss of much information in constructing hashing table. To deal with this shortage, we propose the weighted PCH (WPCH), the grid PCH (GPCH) and the weighted grid PCH (WGPCH).
Keywords :
file organisation; image retrieval; principal component analysis; PCA-based hashing methods; WGPCH; WPCH; grid PCH; hash function; hashing table; weighted PCH; weighted grid PCH; weighted grid principal component analysis hashing; Abstracts; Lead; Mobile communication; Principal component analysis; Hashing; Large Scale Image Retrieval; PCA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
Conference_Location :
Lanzhou
ISSN :
2160-133X
Print_ISBN :
978-1-4799-4216-9
Type :
conf
DOI :
10.1109/ICMLC.2014.7009117
Filename :
7009117
Link To Document :
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