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Proceedings Paper

Study of the model of probability-based covering algorithm
Author(s): Ying Zhou; Yangqun Xie; Ling Zhang
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Paper Abstract

Probability-Based Covering Algorithm (PBCA) is a new algorithm based on probability distribution. It uses the probability of samples and decides the class of the sample on the border of coverage by voting. In the original covering algorithm, there are many tested samples that can't be classified by the spherical neighborhood gained. The network structure of PBCA is mixed structure composed of feed-forward network and feedback network. The method of adding some samples of different class and enlarging the coverage radius is used to decrease the number of refused samples and improve the rates of recognition. The algorithm is effected in improving the study precision.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67880M (15 November 2007); doi: 10.1117/12.747387
Show Author Affiliations
Ying Zhou, Anhui Univ. (China)
Yangqun Xie, Anhui Univ. (China)
Ling Zhang, Anhui Univ. (China)

Published in SPIE Proceedings Vol. 6788:
MIPPR 2007: Pattern Recognition and Computer Vision
S. J. Maybank; Mingyue Ding; F. Wahl; Yaoting Zhu, Editor(s)

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