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Current automatic diagnosis techniques are predominantly of a statistical nature and, despite typical defect densities, do not explicitly consider multiple faults, as also demonstrated by the popularity of the single-fault Siemens set. We present a logic reasoning approach, called Zoltar-M(ultiple fault), that yields multiple-fault diagnoses, ranked in order of their probability. Although application...
One objective for classifying textures in natural images is to achieve the best performance possible. The combination of multiple classifiers has been tested as a suitable technique. This is because the individual behaviors of the different classifiers are exploited by joining performances. Two main problems are to be addressed for combining different classifiers. First, which set of classifiers are...
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