Buildings, Vol. 15, Pages 1905: DSS-MobileNetV3: An Efficient Dynamic-State-Space- Enhanced Network for Concrete Crack Segmentation

Buildings doi: 10.3390/buildings15111905

Authors:
Haibo Li
Yong Cheng
Qian Zhang
Lingkun Chen

Crack segmentation is crucial for health monitoring and preventive maintenance of concrete structures. However, the complex morphologies of cracks and the limited resources of mobile devices pose challenges for accurate and efficient segmentation. To address this, we propose an efficient dynamic-state-space-enhanced network termed DSS-MobileNetV3 for crack segmentation. The DSS-MobileNetV3 adopts a U-shaped encoder–decoder architecture, and a dynamic-state-space (DSS) block is designed into the encoder to improve the MobileNetV3 bottleneck module in modeling global dependencies. The DSS block improves the MobileNetV3 model in structural perception and global dependency modeling for complex crack morphologies by integrating dynamic snake convolution and a state space model. The decoder utilizes the upsampling and depthwise separable convolution to progressively decode and efficiently restore the spatial resolution. In addition, to suppress complex noise in the image background and highlight crack textures, the strip pooling module is introduced into the skip connection between the encoder and decoder for performance enhancement. Extensive experiments are conducted on three public crack datasets, and the proposed DSS-MobileNetV3 achieves SOTA performance in both accuracy and efficiency.

Source link

Haibo Li www.mdpi.com