Contextual Classification of Cracks | Zendy

Noel Bryson | Zendy; Russell Dixon | Zendy; J.J. Hunter | Zendy; Chris Taylor | Zendy

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Contextual Classification of Cracks

Author(s) -

Noel Bryson,

Russell Dixon,

J.J. Hunter,

Chris Taylor

Publication year - 1993

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5244/c.7.41

Subject(s) - computer science , context (archaeology) , set (abstract data type) , bayesian network , artificial intelligence , bayesian probability , pattern recognition (psychology) , statistical classification , data set , machine learning , data mining , geology , paleontology , programming language

We describe a technique for improving the classification of fragmented cues for cracks. Evidence propagation on Bayesian networks represent search within the context of each cue. The algorithm was applied to a data-set of cracks, and results demonstrate that contextual classification of the cues leads to significantly improved error rates.

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