Research graph
References from SpecU-Former: A degradation-aware method for underwater concrete crack segmentation and mask-based width quantification. Local targets link to admitted publications; unresolved targets remain external evidence.
A revised underwater image formation model
2018 · External reference
Swin-Unet: Unet-like pure transformer for medical image segmentation
2023 · External reference
A review of detection technologies for underwater cracks on concrete dam surfaces
10.3390/app13063564 · 2023 · External reference
Unresolved reference
2021 · External reference
Encoder-decoder with atrous separable convolution for semantic image segmentation
2018 · External reference
Crack analysis of tall concrete wind towers using an ad-hoc deep multiscale encoder-decoder with depth separable convolutions under severely imbalanced data
10.1177/14759217241271000 · 2025 · External reference
ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data
10.1016/j.isprsjprs.2020.01.013 · 2020 · External reference
An image is worth 16x16 words: Transformers for image recognition at scale
2021 · External reference
UTNet: A hybrid transformer architecture for medical image segmentation
2021 · External reference
Crackwave R-convolutional neural network: A discrete wavelet transform and deep learning fusion model for underwater dam crack detection
10.1177/14759217241308132 · 2026 · External reference
A cascading risk model for the failure of the concrete spillway of the Toddbrook dam, England during the August 2019 flooding
10.1016/j.ijdrr.2022.103214 · 2022 · External reference
Squeeze-and-excitation networks
2018 · External reference
SDCrackSeg: A frequency- and spatial geometry-aware topology-preserving network for building crack segmentation
10.3390/buildings16050971 · 2026 · External reference
FNet: Mixing tokens with Fourier transforms
2022 · External reference
An underwater image enhancement benchmark dataset and beyond
10.1109/tip.2019.2955241 · 2020 · External reference
Underwater crack pixel-wise identification and quantification for dams via lightweight semantic segmentation and transfer learning
10.1016/j.autcon.2022.104600 · 2022 · External reference
Underwater image enhancement based on adaptive color correction and improved retinex algorithm
10.1109/access.2023.3258698 · 2023 · External reference
Research progress on non-destructive testing technology and application for underwater structural defects
2025 · External reference
CrackFormer: Transformer network for fine-grained crack detection
2021 · External reference
Remotely operated vehicle (ROV) underwater vision-based micro-crack inspection for concrete dams using a customizable CNN framework
10.1016/j.autcon.2025.106102 · 2025 · External reference
Abrasion damage of concrete for hydraulic structures and mitigation measures: A comprehensive review
10.1016/j.conbuildmat.2024.135754 · 2024 · External reference
Swin transformer: Hierarchical vision transformer using shifted windows
2021 · External reference
Lightweight network for millimeter-level concrete crack detection with dense feature connection and dual attention
10.1016/j.jobe.2024.109821 · 2024 · External reference
A framework for automatic real-time pixel-level segmentation of underwater dam concrete cracks utilizing the CRTransU-Net model
10.1016/j.aei.2025.103415 · 2025 · External reference
Crack segmentation of imbalanced data: The role of loss functions
10.1016/j.engstruct.2023.116988 · 2023 · External reference
Global filter networks for image classification
2021 · External reference
Spectral representations for convolutional neural networks
2015 · External reference
U-net: Convolutional networks for biomedical image segmentation
2015 · External reference
Automatic road crack detection using random structured forests
10.1109/tits.2016.2552248 · 2016 · External reference
Two-step rapid inspection of underwater concrete bridge structures combining sonar, camera, and deep learning
10.1111/mice.13401 · 2025 · External reference
Review of intelligent detection and health assessment of underwater structures
10.1016/j.engstruct.2024.117958 · 2024 · External reference
UCTransNet: Rethinking the skip connections in U-net from a channel-wise perspective with transformer
10.1609/aaai.v36i3.20144 · 2022 · External reference
Dual-path network combining CNN and transformer for pavement crack segmentation
10.1016/j.autcon.2023.105217 · 2024 · External reference
CBAM: Convolutional block attention module
2018 · External reference
Enhanced precision in dam crack width measurement: Leveraging advanced lightweight network identification for pixel-level accuracy
10.1155/2023/9940881 · 2023 · External reference
A crack-segmentation algorithm fusing transformers and convolutional neural networks for complex detection scenarios
10.1016/j.autcon.2023.104894 · 2023 · External reference
Feature pyramid and hierarchical boosting network for pavement crack detection
10.1109/tits.2019.2910595 · 2020 · External reference
On-device crack segmentation for edge structural health monitoring
2025 · External reference
Design of control system for underwater inspection robot in hydropower dam structures
10.3390/jmse13091656 · 2025 · External reference
Pyramid scene parsing network
2017 · External reference
UNet++: Redesigning skip connections to exploit multiscale features in image segmentation
10.1109/tmi.2019.2959609 · 2020 · External reference
DeepCrack: Learning hierarchical convolutional features for crack detection
10.1109/tip.2018.2878966 · 2019 · External reference
A framework for automatic real-time pixel-level segmentation of underwater dam concrete cracks utilizing the CRTransU-Net model
10.1016/j.aei.2025.103415 · ExternalCitation · doi-reference
Underwater crack pixel-wise identification and quantification for dams via lightweight semantic segmentation and transfer learning
10.1016/j.autcon.2022.104600 · ExternalCitation · doi-reference
A crack-segmentation algorithm fusing transformers and convolutional neural networks for complex detection scenarios
10.1016/j.autcon.2023.104894 · ExternalCitation · doi-reference
Dual-path network combining CNN and transformer for pavement crack segmentation
10.1016/j.autcon.2023.105217 · ExternalCitation · doi-reference
Remotely operated vehicle (ROV) underwater vision-based micro-crack inspection for concrete dams using a customizable CNN framework
10.1016/j.autcon.2025.106102 · ExternalCitation · doi-reference
Abrasion damage of concrete for hydraulic structures and mitigation measures: A comprehensive review
10.1016/j.conbuildmat.2024.135754 · ExternalCitation · doi-reference
Crack segmentation of imbalanced data: The role of loss functions
10.1016/j.engstruct.2023.116988 · ExternalCitation · doi-reference
Review of intelligent detection and health assessment of underwater structures
10.1016/j.engstruct.2024.117958 · ExternalCitation · doi-reference
A cascading risk model for the failure of the concrete spillway of the Toddbrook dam, England during the August 2019 flooding
10.1016/j.ijdrr.2022.103214 · ExternalCitation · doi-reference
ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data
10.1016/j.isprsjprs.2020.01.013 · ExternalCitation · doi-reference
Lightweight network for millimeter-level concrete crack detection with dense feature connection and dual attention
10.1016/j.jobe.2024.109821 · ExternalCitation · doi-reference
Underwater image enhancement based on adaptive color correction and improved retinex algorithm
10.1109/access.2023.3258698 · ExternalCitation · doi-reference
DeepCrack: Learning hierarchical convolutional features for crack detection
10.1109/tip.2018.2878966 · ExternalCitation · doi-reference
An underwater image enhancement benchmark dataset and beyond
10.1109/tip.2019.2955241 · ExternalCitation · doi-reference
Automatic road crack detection using random structured forests
10.1109/tits.2016.2552248 · ExternalCitation · doi-reference
Feature pyramid and hierarchical boosting network for pavement crack detection
10.1109/tits.2019.2910595 · ExternalCitation · doi-reference
UNet++: Redesigning skip connections to exploit multiscale features in image segmentation
10.1109/tmi.2019.2959609 · ExternalCitation · doi-reference
Two-step rapid inspection of underwater concrete bridge structures combining sonar, camera, and deep learning
10.1111/mice.13401 · ExternalCitation · doi-reference
Enhanced precision in dam crack width measurement: Leveraging advanced lightweight network identification for pixel-level accuracy
10.1155/2023/9940881 · ExternalCitation · doi-reference
Crack analysis of tall concrete wind towers using an ad-hoc deep multiscale encoder-decoder with depth separable convolutions under severely imbalanced data
10.1177/14759217241271000 · ExternalCitation · doi-reference
Crackwave R-convolutional neural network: A discrete wavelet transform and deep learning fusion model for underwater dam crack detection
10.1177/14759217241308132 · ExternalCitation · doi-reference
UCTransNet: Rethinking the skip connections in U-net from a channel-wise perspective with transformer
10.1609/aaai.v36i3.20144 · ExternalCitation · doi-reference
A review of detection technologies for underwater cracks on concrete dam surfaces
10.3390/app13063564 · ExternalCitation · doi-reference
SDCrackSeg: A frequency- and spatial geometry-aware topology-preserving network for building crack segmentation
10.3390/buildings16050971 · ExternalCitation · doi-reference
Design of control system for underwater inspection robot in hydropower dam structures
10.3390/jmse13091656 · ExternalCitation · doi-reference
