Abstract: A baseline visualization is parsed to identify visual elements in the baseline visualization. A user interface allows a user to configure a lens overlay that associates an overlay shape, with corresponding data obtained through an API, from an external source. The data and shape in the lens overlay are also associated with a visual element in the baseline visualization. The lens overlay is separate from the baseline visualization. When the baseline visualization is displayed, the lens overlay, is displayed concurrently with the baseline visualization so that shapes in the lens overlay are displayed at a configured location and position relative to visual elements in the baseline visualization.

Abstract: A method is provided of forming a neural network for detecting surface defects in aircraft engine components. The method includes: providing (i) a pre-trained deep learning network and (ii) a learning machine network; providing a set of pixelated training images of aircraft engine components exhibiting examples of different classes of surface defect; training the trainable weights of the learning machine network on the set of training images.

Abstract: A method is provided of forming a neural network for detecting surface defects in aircraft engine components. The method includes: providing (i) a pre-trained deep learning network and (ii) a learning machine network; providing a set of pixelated training images of aircraft engine components exhibiting examples of different classes of surface defect; training the trainable weights of the learning machine network on the set of training images.