Abstract: Systems and methods for image recognition are provided. A style-transfer neural network is trained for each real image to obtain a trained style-transfer neural network. The texture or style features of the real images are transferred, via the trained style-transfer neural network, to a target image to generate styled images which are used for training an image-recognition machine learning N model (e.g., a neural network). In some cases, the real images are clustered and representative style images are selected from the clusters.

Abstract: The present disclosure includes in one instance an optical article comprising a data rich plurality of retroreflective meats that are configured in a spatially defined arrangement, where the plurality of retroreflective elements comprise retroreflective elements having at least two different retroreflective properties, and where data rich means information that is readily machine interpretable. The present disclosure also includes a system comprising the previously mentioned optical article, an optical system, and an inference engine for interpreting and classifying the plurality of retroreflective elements wherein the optical system feeds data to the inference engine.

Abstract: A method for aligning digital 3D models of dental arch pairs, including a mandible and maxilla, to bring them into bite alignment. The method estimates representative planes for the mandible and maxilla 3D models and transforms the models such that the representative planes are each aligned with their respective coordinate systems and shown in a horizontal view. The method also transforms the models such that the mandible and maxilla are each aligned with a same coordinate system and shown in a front view. The digital 3D models are then brought into bite alignment such that the mandible is in occlusion with the maxilla or within a distance near to occlusion. The digital models of the bite-aligned arch pairs can also be transformed or rotated to be shown centered in a front view.

Abstract: This disclosure provides systems and methods for monitoring respiratory parameters of a person (e.g., a user). In some examples, a system for respiratory monitoring includes a sensor and a computing device. The sensor monitors at least one respiratory related parameter. The computing device is connected to the sensor. The computing device includes a processor. The processor receives a feature vector having a plurality of features, each respective feature associated with a respective respiratory related parameter. The processor also receives from the sensor the at least one respective respiratory related parameter. The processor determines a first breathing state based on the feature vector.

Abstract: A method for aligning digital 3D models of dental arch pairs, including a mandible and maxilla, to bring them into bite alignment. The method estimates representative planes for the mandible and maxilla 3D models and transforms the models such that the representative planes are each aligned with their respective coordinate systems and shown in a horizontal view. The method also transforms the models such that the mandible and maxilla are each aligned with a same coordinate system and shown in a front view. The digital 3D models are then brought into bite alignment such that the mandible is in occlusion with the maxilla or within a distance near to occlusion. The digital models of the bite-aligned arch pairs can also be transformed or rotated to be shown centered in a front view.