Abstract: Integration code usable to cause a computing device to determine which category from a plurality of categories corresponds to an interface of an interface provider is generated based at least in part on output from a machine learning algorithm trained to categorize interfaces. The computing device is caused, by providing the integration code to the computing device, to execute the integration code to cause the computing device to evaluate characteristics of an interface of an interface provider, determine a category of an interface of the interface provider, and interact with the interface in a manner that accords with the category.

Abstract: A system (100) and method for zooming of a video recording are provided. The system is configured to detect, track and select object(s) in a first view (110) of the video recording. The system further is configured to perform at least one of an in-zooming and an out-zooming of the video recording relative the first view of the video recording. The system is configured to stop a performed in-zooming or out-zooming, in case at least one predetermined event occurs during the video recording.

Abstract: A first characteristic associated with a first interface of an interface type and a second characteristic associated with a second interface of an additional interface type are determined. A machine learning algorithm is trained using the first characteristic, the second characteristic, and the interface type as a ground truth for the first characteristic. A template script usable to identify whether a given interface of the same interface provider is of the interface type or the additional interface type is generated. The parameter for the template script is determined based the machine learning algorithm. A device is caused to, as a result of the device executing the template script with the parameter to identify that the given interface is of the interface type, perform an operation specific to the interface type.