Recognition and Classification of Concrete Surface Cracks with an Inception Quantum Convolutional Neural Network Algorithm

Author:

Bu Yun-zhe,Xiao Yi-lei,Li Ya-jun,Meng Ling-guang

Publisher

Springer Science and Business Media LLC

Reference28 articles.

1. Adhikari, R.S., Moselhi, O., and Bagchi, A., 2014, Image-based retrieval of concrete crack properties for bridge inspection[J]: Automation in construction, 39, 180–194.

2. Alipour, M., Harris, D.K., 2019, Increasing the robustness of material-specific deep learning models for crack detection across different materials[J]: Engineering structures, 206(0), 110157.

3. Chen, F.-C. and Jahanshahi, M. R., 2018, Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion: IEEE Transactions on Industrial Electronics, 65(05), 4392–4400.

4. Fan, X.K., Liu, G.Z. and Wang, H.W., et. al., 2022, A New Model of Image Recognition Based on Quantum Convolutional Neural Network[J]: Journal of University of Electronic Science and Technology of China, 51(05), 642–650.

5. Goyal, B., Dogra, A., and Agrawal, S., et al., 2020, Image denoising review: From classical to state-of-the-art approaches[J]: Information fusion, 55, 220–244.

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