Abstract: A method for operating a computing system on at least one processor includes performing search space reduction on input data using a first trained artificial intelligence model to generate relevant regions in the input data. The method also includes generating region proposals in the relevant regions using a second trained artificial intelligence model. The method further includes performing unsupervised anomaly classification on the region proposals using a third trained artificial intelligence model to classify each of the region proposals as normal or as an anomaly. The method further includes performing contextual filtering on the region proposals classified as anomalies to determine if any of the region proposals classified as anomalies are contextually normal using a fourth trained artificial intelligence model.

Abstract: A computing system includes a processor that executes program instructions and memory for storing the program instructions. The program instructions include an artificial neural network (ANN) that receives input data. The ANN maps the input data to a latent representation of the input data. The ANN maps the latent representation of the input data to a reconstruction of the input data. The computing system adapts learning features of an artificial intelligence model based on an output of the ANN.