Encoder-decoder network for pixel-level road crack detection in black-box images
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Title
Encoder-decoder network for pixel-level road crack detection in black-box images
Authors
Keywords
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Journal
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
Volume -, Issue -, Pages -
Publisher
Wiley
Online
2019-02-28
DOI
10.1111/mice.12440
References
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- (2018) Allen Zhang et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection
- (2018) Qin Zou et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
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- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- (2017) Vijay Badrinarayanan et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Automated Detection of Multiple Pavement Defects
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