Amazon Technologies, Inc.

Christian Leistner

Joseph Rutland

Aniruddh Raghu

Andres Perez Torres

A convolutional neural network may be trained to inspect subjects such as carbon fiber propellers for surface flaws or other damage. The convolutional neural network may be trained using images of damaged and undamaged subjects. The damaged subjects may be damaged authentically during operation or artificially by manual or automated means. Additionally, images of undamaged subjects may be synthetically altered to depict damages, and such images may be used to train the convolutional neural network. Images of damaged and undamaged subjects may be captured for training or inspection purposes by an imaging system having cameras aligned substantially perpendicular to subjects and planar light sources aligned to project light upon the subjects in a manner that minimizes shadows and specular reflections. Once the classifier is trained, patches of an image of a subject may be provided to the classifier, which may predict whether such patches depict damage to the subject.

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Graz, Austria

Christian Leistner