Multi-scale local feature enhanced transformer network for pavement crack detection

Author:

Zhengsen Xu, ,Xiangda Lei,Haiyan Guan

Publisher

Aerospace Information Research Institute, Chinese Academy of Sciences

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference28 articles.

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2. Cao H,Wang Y Y,Chen J,Jiang D S,Zhang X P,Tian Q and Wang M N. 2021. Swin-Unet:Unet-like pure transformer for medical image segmentation[EB/OL].[2021-05-21].https://arxiv.org/pdf/2105.05537.pdf

3. Dosovitskiy A,Beyer L,Kolesnikov A,Weissenborn D,Zhai X H,Unterthiner T,Dehghani M,Minderer M,Heigold G,Gelly S,Uszkoreit J and Houlsby N. 2021. An image is worth 16×16 words:transformers for image recognition at scale//Proceedings of the 9th International Conference on Learning Representations.[s. l.]:OpenReview.net:1-21

4. Du Y C,Pan N,Xu Z H,Deng F W,Shen Y and Kang H. 2021. Pavement distress detection and classification based on YOLO network.International Journal of Pavement Engineering,22(13):1659-1672[DOI:10.1080/10298436.2020.1714047]

5. Fang F,Li L Y,Gu Y,Zhu H Y and Lim J H. 2020. A novel hybrid approach for crack detection. Pattern Recognition,107:#107474[DOI:10.1016/j.patcog.2020.107474]

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