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Fourth International Conference on Computer and Information Technology (CIT'04)
Dimension Reduction Based on Rough Set in Image Mining
Wuhan, China
September 14-September 16
ISBN: 0-7695-2216-5
| ASCII Text | x | ||
| Maofu Liu, Yanxiang He, Huijun Hu, Dandan Yu, "Dimension Reduction Based on Rough Set in Image Mining," Computer and Information Technology, International Conference on, pp. 39-44, Fourth International Conference on Computer and Information Technology (CIT'04), 2004. | |||
| BibTex | x | ||
| @article{ 10.1109/CIT.2004.1357172, author = {Maofu Liu and Yanxiang He and Huijun Hu and Dandan Yu}, title = {Dimension Reduction Based on Rough Set in Image Mining}, journal ={Computer and Information Technology, International Conference on}, volume = {0}, year = {2004}, isbn = {0-7695-2216-5}, pages = {39-44}, doi = {http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357172}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Computer and Information Technology, International Conference on TI - Dimension Reduction Based on Rough Set in Image Mining SN - 0-7695-2216-5 SP39 EP44 A1 - Maofu Liu, A1 - Yanxiang He, A1 - Huijun Hu, A1 - Dandan Yu, PY - 2004 KW - Image Mining KW - Rough Set Theory KW - Image Understanding KW - Dimension Reduction KW - Information System VL - 0 JA - Computer and Information Technology, International Conference on ER - | |||
Image mining is a nontrivial process to discover valid, novel, potentially useful, and ultimately understandable knowledge from large image sets or image databases. With the rapid development of rough set theory in recent years, more and more people have applied this theory to different research fields. In order to solve the curse of dimensionality in image mining, in this paper, we give our own solution to this problem based on rough set. After introducing the basic concepts of rough set theory and the attribute reduction of information system, we put forward the related algorithms mainly including the partition algorithm and the dimension reduction algorithm. The experimental result has justified the feasibility of the solution based on rough set.
Index Terms:
Image Mining, Rough Set Theory, Image Understanding, Dimension Reduction, Information System
Citation:
Maofu Liu, Yanxiang He, Huijun Hu, Dandan Yu, "Dimension Reduction Based on Rough Set in Image Mining," cit, pp.39-44, Fourth International Conference on Computer and Information Technology (CIT'04), 2004
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