FLAW LEARNING DEVICE, FLAW LEARNING METHOD AND COMPUTER PROGRAM

摘要

PROBLEM TO BE SOLVED: To select data suited to the updating of a learning model from the data of many flaws when updating the learning model for discriminating a flaw kind from the feature amount of the flaw generated in a flaw inspection object using the data of the feature amount of the flaw for which the correct answer data of the flaw kind are given. SOLUTION: The learning model is generated as a set of a plurality (L pieces) of partial feature amount spaces for making the set of the range of values of feature amounts for completely separating the flaw kinds "CL1", "CL2" and the flaw kinds "CL1", "CL2" correspond to each other. Then, the learning model is updated using only the flaw data with low reliability over the discrimination result of a flaw kind in the learning model in the feature amount space among the inputted flaw data. COPYRIGHT: (C)2011,JPO&INPIT