Abstract: Presented herein are systems and methods for generating synthetic training data for machine learning models. Images of a particular object (such as an aircraft) can be received and processed to cutout the object (i.e., separate the object from the background) from the received image. The systems and methods described herein can detect areas in the background images to place an object. Once a suitable area has been detected, the cutout object image can be superimposed on the background image at the location determined to be suitable for placing the object. Superimposing the object onto the background image can include blending the two images using a plurality of blending techniques to reduce artifacts that may bias a supervised training process.

Abstract: Presented herein are systems and methods for identifying and disambiguating individual objects of interest from a data set. In one or more examples, image data can be received and processed to identify candidate images that may contain one or more objects of interest. The candidate image data can then be processed to segment potential objects of interest from the candidate images. The segmented potential objects of interest can then be processed via one or more analytics to determine whether each potential objects of interest is an object of interest, to determine an object type, and/or to disambiguate specific objects of interest.

Abstract: One embodiment of the invention relates to a system, method and software for displaying visual cues to an end-user based on indicia received from a remote source. More particularly, the present invention relates to displaying visual cues on a display coupled to a fixed function processor. According to one embodiment, the fixed-function processor-based system may include an input/output interface. The fixed-function processor-based system may also include a memory including processor-readable software code configured to permit the processor-based system to perform a fixed-function and processor-readable software code configured to enable the fixed-function processor-based system to prioritize a number of visual cues based on an importance factor associated with the application task. The fixed-function processor-based system may also be configured to execute the fixed function and to prioritize the plurality of visual cues based on the importance factor.