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Jan 19, 2022 · An end-to-end network Feature Fusion Encoder Decoder Network (FFEDN) with two novel modules is proposed to improve the crack detection accuracy.
Crack detection plays a crucial role in structural health monitoring tasks to ensure the reliability of the transportation infrastructures.
There- fore, an end-to-end network Feature Fusion Encoder Decoder. Network (FFEDN) with two novel modules is proposed to improve the crack detection accuracy.
Crack detection plays a crucial role in structural health monitoring tasks to ensure the reliability of the transportation infrastructures.
This paper presents an Asymmetric Dual-Decoder-U-Net (ADDU-Net) model, which involves constructing an asymmetric dual decoder with a dual attention module.
May 15, 2023 · Therefore, an end-to-end network Feature Fusion Encoder Decoder Network (FFEDN) with two novel modules is proposed to improve the crack ...
An efficient and effective end-to-end network for automatic pavement crack segmentation, called RHA-Net, is proposed to improve the pavement crack ...
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This study proposed a transfer learning-based encoder-decoder method with visual explanations for infrastructure crack segmentation.
May 15, 2023 · The noise filtering fusion module is embedded in the improved encoder-decoder structure to constitute an end-to-end convolutional neural network ...
3 days ago · FFEDN: Feature Fusion Encoder Decoder Network for Crack Detection ... Crack Detection With Enhanced Convolution and Dynamic Feature Fusion.