End-To-End Aircraft Skin Damage Detection Method Based on Ghostnet

Author:

Hao Wang,Jia Liu,Fu Lanxue

Publisher

Springer Nature Singapore

Reference16 articles.

1. Zhang, W., Wang, M.D., Fan, J.L., et al.: Progress and prospect of the application of machine vision in aircraft structural damage detection.Nondestr. Test. 43(10), 75–80 (2021)

2. Obadimu, S.O., Karanikas, N., Kourousis, K.I.: Development of the minimum equipment list: current practice and the need for standardization. Aerospace 7(1), 7 (2020)

3. Yasuda, Y.D., Cappabianco, F.A., Martins, L.E.G., Gripp, J.A.: Aircraft visual inspection: a systematic literature review. Comput. Ind. 141(15), 103695 (2022)

4. Tang, L.: Research on Inspection of Damaged Fasteners for Aircraft Skin Based on Convolutional Neural Network, Nanjing University of Aeronautics and Astronautics (2020)

5. Anil, D., Soufiane, B., Ridwan, A.: Using convolutional neural networks to automate aircraft maintenance visual inspection. Aerospace 7(12), 171 (2020)

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