Abstract: Method and system that includes receiving an sensed data point from an industrial process; applying a mapping model to map the sensed data point to a respective embedding that has reduced dimensionality relative to the sensed data point; determining, based on a comparison of the respective embedding to prior embeddings, if the mapping model needs to be updated or not. When the mapping model needs to be updated, applying manifold learning to learn an updated set of model parameters for the mapping model. When the mapping model does not need to be updated, applying a classification model to the respective embedding to predict a classification for the sensed data point.

Abstract: System and method that includes mapping temperature values from a two dimensional (2D) thermal image of a component to a three dimensional (3D) drawing model of the component to generate a 3D thermal model of the component; mapping temperature values from the 3D thermal model to a 2D virtual thermal image corresponding to a virtual thermal camera perspective; and predicting an attribute for the component by applying a prediction function to the 2D virtual thermal image.

Abstract: A server for configuring an industrial vision control module includes: a memory; a network interface; and a processor interconnected with the memory and the network interface, the processor configured to: receive, via the network interface, image data from a vision system; determine at least one attribute of the image data; store at least one label in association with the at least one attribute; and transmit the at least one attribute and the at least one label to the vision system.