Aircraft Fuselage Defect Detection using Deep Neural Networks

Understand

To ensure flight safety of aircraft structures, it is necessary to have regular maintenance using visual and nondestructive inspection (NDI) methods.

• In this paper, we propose an automatic image-based aircraft defect detection using Deep Neural Networks (DNNs).
• To the best of our knowledge, this is the first work for aircraft defect detection using DNNs.
• We perform a comprehensive evaluation of state-of-the-art feature descriptors and show that the best performance is achieved by vgg-f DNN as feature extractor with a linear SVM classifier.