Abstract: A method for rating a state of a three-dimensional test object by taking into consideration a prescribed assessment task and by using a rating system comprising a neural network, wherein a training data record comprising multiple state data points from one or more three-dimensional training objects is provided and/or used, wherein the training data record comprises a known state rating in regard to the prescribed assessment task for each of the state data points, wherein the neural network of the rating system is parameterized in a training process by using the training data record in order to adapt the rating system to the prescribed assessment task, and wherein a state rating for a prescribed state data point of the test object is calculated with the adapted rating system in an execution process. In addition, a corresponding rating system and a computer program product are disclosed.

Abstract: A method for rating a state of a three-dimensional test object by taking into consideration a prescribed assessment task and by using a rating system comprising a neural network, wherein a training data record comprising multiple state data points from one or more three-dimensional training objects is provided and/or used, wherein the training data record comprises a known state rating in regard to the prescribed assessment task for each of the state data points, wherein the neural network of the rating system is parameterized in a training process by using the training data record in order to adapt the rating system to the prescribed assessment task, and wherein a state rating for a prescribed state data point of the test object is calculated with the adapted rating system in an execution process. In addition, a corresponding rating system and a computer program product are disclosed.