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The recognition and detection of cracks in historical landscape buildings through deep learning technology
S. Wang 1, D.H. Zhu 1

1 School of Product Design, Shanghai Art & Design Academy, Shanghai, 201808, China

  Full text (PDF)

DOI: 10.18287/COJ1864

Article ID: 1864

Language: English

Abstract:
This paper added the spatial attention fusion module with an attention mechanism to the You Only Look Once version 5 algorithm to improve its building crack detection performance. Simulation experiments were conducted. Ablation experiments were conducted on the improved model to verify the role of the spatial attention fusion module module. It was then compared with three target detection algorithms: Faster-regional-based convolutional neural network, You Only Look Once version 4, and You Only Look Once version 6. It was found that the addition of the spatial attention fusion module module effectively improved the target detection performance of the You Only Look Once version 5 algorithm. The improved You Only Look Once version 5 algorithm identified building crack types more accurately than the Faster-regional-based convolutional neural network algorithm and the You Only Look Once version 4 and 6 algorithms, and made accurate positioning.

Keywords:
building crack, deep learning, crack identification, You Only Look Once version 5.

Citation:
Wang S, Zhu DH. The recognition and detection of cracks in historical landscape buildings through deep learning technology. Computer Optics. 2026; 50(5): 1864. doi: 10.18287/COJ1864.

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