Using artificial intelligence strategies for process-related automated inspection in the production environment
In this paper a new method for the automatic visual inspection of metallic surfaces is proposed by using Convolutional Neural Networks (CNN). The different combinations of network parameters were developed and tested. The obtained results of CNN were analysed and compared with the results of our previous investigations with color and texture features as input parameters for a Support Vector Machine. Advantages and disadvantages of the different classifying methods are explained.
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