Abstract: A device and computer-implemented method for machine learning. The method includes: providing first and second classes; providing a first set of scene graphs including scene graphs of digital images that are incorrectly classified in the first class or the second class; providing a second set of scene graphs including scene graphs of digital images that are correctly classified with respect to the first class or the second class; determining, depending on the first set of scene graphs and the second set of scene graphs a rule that indicates that a presence of a first object and/or a second object in a digital image and/or a relation between the first object and the second object in the scene graph of the digital image results in that the classification of the digital image includes a misclassification of the digital image into the second class instead of the first class.

Abstract: A device and method for operating a machine. The method comprises providing a digital image, providing a structured representation of a question, predicting with an object detector and depending on at least a part of the digital image an area of the digital image wherein an object is depicted in the digital image, predicting with a classifier and depending on at least a part of the digital image within the area a first score indicating a likelihood that the object is of a first class and a second score indicating a likelihood that the object is of a second class, providing at least one attribute value for the first class, adding to an answer set programming program a first rule comprising the at least one attribute value of the first class and/or a first constraint comprising the at least one attribute value of the first class.