Detection of Defects by Natural Language Description

Abstract

A method for detecting faulty manufactured items based on natural language descriptions (NLDs), the method may include: (i) obtaining one or more neural networks (NNs) that are trained to detect objects that exhibit one or more textual features of a group of textual features; wherein members of the group are defined by NLDs; wherein the one or more NNs are trained on one or more training datasets, the training datasets are not based on sensed information units (SIUs) of the manufactured items; (ii) receiving a SIU that captures an evaluated manufactured item (EMI); (iii) processing the SIU of the EMI by the one or more NNs, to provide one or more NN processing results regarding one or more relationships between the EMI and the one or more textual features; and (iv) determining a status of the EMI, based on one or more decision rules and the one or more NN processing results.

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