Abstract: In an approach to identifying occluded objects, a computer retrieves a first image that includes an object at least partially occluded by one or more occlusions. A computer removes the one or more occlusions from the first image to create a partial object in a second image. A computer runs a detection model with the second image to predict one or more identifications of a symbol represented by the partial object. A computer determines top predictions of the one or more identifications of the symbol by the detection model. A computer identifies at least one geometric property associated with the one or more identifications of the symbol included in the one or more top predictions. A computer applies the at least one geometric property to the partial object. A computer determines a probability of the one or more top predictions correctly identifying the symbol represented by the partial object.

Abstract: Certain embodiments herein relate to dynamically updating a software application to utilize new advertising capabilities or features at runtime. A software application may be developed using libraries in a software development kit (SDK) that include particular functionality related to advertising. As new ad related features become available (such as displaying or handling new ad types or tracking new metrics associated with ads), the new features may be injected or loaded into the application at runtime. Such loading may configure a device running the application to take advantage of the new ad features without re-downloading, reinstalling, or performing other initialization functions associated with the application and/or its library functions.