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<div><p>Traditional crack detection methods initially relied on manual observation, followed by instrument-assisted techniques. Today, road surface inspection leverages deep learning to achieve automated crack detection. However, in the domain of deep learning-based road surface damage c...

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Bibliographic Details
Main Author:	Jinwen Wang (2159593) (author)
Other Authors:	Xiaowei Li (620087) (author), Yong Xu (17491) (author), Zhiyu Zhou (291914) (author), Wenlin Wu (461424) (author), Zheng Li (26302) (author)
Published:	2025
Subjects:	Biochemistry Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified scale receptive fields performance improvements associated learn edge information global structural information factors often undermine experimental results demonstrate enhances edge information scale feature fusion scale feature extraction feature extraction phase local edge features proposed model achieved model &# 8217 background dataset rdd2020 background dataset concrete_data_week3 improving classification accuracy rdd2020 dataset concrete_data_week3 dataset classification accuracy feature maps unstructured features background interference thereby mitigating thereby enhancing process captures paper proposes optimizing cnn msff ), manual observation independent contributions generalization capability effectively strengthens deep learning dcnns ). crack regions assisted techniques ablation studies
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