Abstract: Systems and methods employ knowledge distillation for efficient machine learning. Systems and methods integrate self-supervised learning, supervised learning, semi-supervised learning and active learning, each of which learning is executed in an iterative fashion. The system comprises three main components: a database server, a data analytics system and a standard dashboard. The database server contains real-time inventory images as well as historical images of each product type. The data analytics system is executed by a computer processor configured to apply a multi-head self-supervised learning-based deep neural network. The standard dashboard is configured to output a report regarding the object information.

Abstract: A device may receive a set of images for an object recognition operation to identify one or more objects in the set of images after the set of images are combined into a stitched image. The device may combine the set of images into the stitched image. The device may determine reliability scores for the set of images. The reliability scores may be determined based on a difference in images of the set of images, and the reliability scores may predict a quality of the stitched image that includes an image, of the set of images, to which the reliability scores correspond. The device may determine whether a result of the object recognition operation is likely to satisfy a threshold based on the reliability scores. The device may selectively perform the object recognition operation based on whether the result of the object recognition operation is likely to satisfy the threshold.

Abstract: A device may receive a set of images for an object recognition operation to identify one or more objects in the set of images after the set of images are combined into a stitched image. The device may combine the set of images into the stitched image. The device may determine reliability scores for the set of images. The reliability scores may be determined based on a difference in images of the set of images, and the reliability scores may predict a quality of the stitched image that includes an image, of the set of images, to which the reliability scores correspond. The device may determine whether a result of the object recognition operation is likely to satisfy a threshold based on the reliability scores. The device may selectively perform the object recognition operation based on whether the result of the object recognition operation is likely to satisfy the threshold.