Study of the model of probability-based covering algorithm

Ying Zhou; Yangqun Xie; Ling Zhang

doi:10.1117/12.747387

15 November 2007 Study of the model of probability-based covering algorithm

Ying Zhou, Yangqun Xie, Ling Zhang

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 67880M (2007) https://doi.org/10.1117/12.747387
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Ying Zhou, Yangqun Xie, and Ling Zhang "Study of the model of probability-based covering algorithm", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67880M (15 November 2007); https://doi.org/10.1117/12.747387

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