Abstract: Techniques disclose an incrementally expanding object detection model. An object detection tool identifies, based on an object detection model, one or more objects in a sequence of video frames. The object detection model provides an object space including a plurality of object classes. Each object class includes one or more prototypes. Each object is classified as being an instance of one of the object classes. Each identified object is tracked across at least one of the frames. The object detection tool generates a measure of confidence for that object based on the tracking. Upon determining that the measure of confidence exceeds a threshold, the object detection tool adds a prototype of the instance to the object detection model.

Abstract: Disclosed herein are a lamination apparatus which adheres substrates to a cover window having a curved surface and a lamination method using the same. The lamination apparatus includes a first jig on which a cover window is mounted, wherein a curved surface portion is formed in the cover window and a curvature center thereof is positioned behind the curved surface portion, a second jig on which a guide member is seated, wherein a substrate is mounted on the guide member and the guide member has a width greater than that of the substrate, and an interference member provided to interfere with both facing front surfaces of the guide member, wherein the interference member interferes with the guide member and the guide member is bent when the second jig approaches the first jig.

Abstract: There are provided systems and methods for performing object classification through semantic mapping. Such an object classification system includes a system processor, a system memory, and an object categorizing unit stored in the system memory. The system processor is configured to execute the object categorizing unit to receive image data corresponding to an object, and to transform the image data into a directed quantity expressed at least in part in terms of semantic parameters. The system processor is further configured to determine a projection of the directed quantity onto an object representation map including multiple object categories, and to associate the object with a category from among the multiple object categories based on the projection.

Abstract: There are provided systems and methods of incremental category embedding for categorization. One method including selecting one or more input categories from a plurality of input categories to be added to learned categories, determining at least one representative category from the learned categories for each input category from the one or more input categories, the at least one representative category representing the input category, and approximating the input category using the at least one representative category.

Abstract: There are provided systems and methods of incremental category embedding for categorization. One method including selecting one or more input categories from a plurality of input categories to be added to learned categories, determining at least one representative category from the learned categories for each input category from the one or more input categories, the at least one representative category representing the input category, and approximating the input category using the at least one representative category.