A Lightweight Deep Learning-Based Approach for Concrete Crack Characterization Using Acoustic Emission Signals
This paper proposes an acoustic emission (AE) based automated crack characterization method for reinforced concrete (RC) beams using a memory efficient lightweight convolutional neural network named SqueezeNet. The proposed method also includes a signal-to-image technique, which is continuous wavele...
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| Auteurs principaux: | , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
IEEE
2021-01-01
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| Collection: | IEEE Access |
| Sujets: | |
| Accès en ligne: | https://ieeexplore.ieee.org/document/9493229/ |
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