Abstract
Rapid and accurate segmentation of structural cracks is essential for ensuring the quality and safety of engineering projects. In practice,however,this task faces the challenge of finding a balance between detection accuracy and effi-ciency. To alleviate this problem,a lightweight and efficient real-time crack segmentation framework was developed. Specifically,in the network model system based on an encoding-decoding structure,the encoding network is equipped with packet convolution and attention mechanisms to capture features of different visual scales in layers,and in the decoding process,we also introduce a fusion module based on spatial attention to effectively aggregate these hierarchical features. Codecs are connected by pyramid pooling model (PPM) filtering. The results show that the crack segmentation accuracy and real-time operation capability larger than 76％ and 15 fps,respectively,are vali-dated by three publicly available datasets. These wide-ranging results highlight the potential of the model for the intelligent O&M for cross-sea bridge.
维普
万方数据