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Asymmetric dual-decoder-U-Net for pavement crack semantic segmentation

  • Published:2023-12 Issue: Volume:156 Page:105138
  • ISSN:0926-5805
  • Container-title:Automation in Construction
  • language:en
  • Short-container-title:Automation in Construction

Author:

Al-Huda ZaidORCID,Peng Bo,Algburi Riyadh Nazar Ali,Al-antari Mugahed A.ORCID,AL-Jarazi Rabea,Al-maqtari OmarORCID,Zhai DonghaiORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Sichuan Province

Sichuan Province Science and Technology Support Program

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference59 articles.

1. DMA-Net: DeepLab with multi-scale attention for pavement crack segmentation;Sun;IEEE Trans. Intell. Transp. Syst.,2022

2. Semantic segmentation of cracks: Data challenges and architecture;Panella;Autom. Constr.,2022

3. Weakly supervised pavement crack semantic segmentation based on multi-scale object localization and incremental annotation refinement;Al-Huda;Appl. Intell.,2023

4. Yolov3: An incremental improvement;Redmon,2018

5. Bag of tricks for image classification with convolutional neural networks;He,2019

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