Abstract: One or more systems, devices, computer program products, and/or computer-implemented methods provided herein relate to accurate anomaly detection in images using patched features. According to an embodiment, an extraction component can extract multiple layers of features from one or more patches of an image using a pretrained convolutional neural network (CNN). A feature mapping component can concatenate the features from the multiple layers to generate a tensor feature map comprising a one-dimensional feature vector for respective patches. A cropping component can perform center cropping on the tensor feature map. A calculation component can calculate a distance to a feature distribution mean for respective patches.

Abstract: A computerized machine learning anomaly detection model trained on a plurality of samples of one or more source domains (optionally, one or more source domains and the target domain) is accessed. Using online deep sets, one or more domain vectors are computed for each target domain sample at an observation point, each target domain sample corresponding to a given target domain, where the one or more domain vectors represent a similarity and difference among the source and target domains. The target domain sample is processed using the anomaly detection model trained on the plurality of samples of the source to generate an anomaly score, the processing being based on the computed one or more domain vectors.

Abstract: A method includes receiving, by a computing device, acceleration information from an acceleration sensor attached to a product; receiving, by the computing device, from an image capture device an image of a prospective purchaser of the product; determining, by the computing device, a movement of the prospective purchaser based on the acceleration information and the image, the movement being in relation to a movement of the product; and sending, by the computing device, display information to a digital display, the display information including information related to the product. The movement of the product is based on the acceleration information.

Abstract: A method includes receiving, by a computing device, acceleration information from an acceleration sensor attached to a product; receiving, by the computing device, from an image capture device an image of a prospective purchaser of the product; determining, by the computing device, a movement of the prospective purchaser based on the acceleration information and the image, the movement being in relation to a movement of the product; and sending, by the computing device, display information to a digital display, the display information including information related to the product. The movement of the product is based on the acceleration information.