Abstract: The embodiments execute machine-learning architectures for training and managing machine-learning architectures for object recognition and other image processing operations. A computer receives image data (e.g., still images, videos) with imagery of a target object. The computer generates a rendering of a virtual environment containing a simulated obj ect representing the target object. The computer generates a simulated video recording containing a “fly around” of the simulated object. Using the simulated video recording, the computer generates simulated still images as snapshots of the simulated object at various angles. The computer trains the machine-learning architecture to recognize the target object by applying the machine-learning architecture on the simulated still images containing the simulated object.

Abstract: A residential home characteristics inferring method and system that receives information about energy usage by an energy user, determines using a processor and the received information about energy usage average daily usage during a heating season and average daily usage during a shoulder season, and identifies the fuel type used for heating by the energy user using the determined average daily usage during the heating season and the determined average daily usage during the shoulder season.