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Zhou et al., 2023 - Google Patents

Deep learning-based crack segmentation for civil infrastructure: Data types, architectures, and benchmarked performance

Zhou et al., 2023

Document ID
2494630325257189842
Author
Zhou S
Canchila C
Song W
Publication year
Publication venue
Automation in Construction

External Links

Snippet

This paper reviews recent developments in deep learning-based crack segmentation methods and investigates their performance under the impact from different image types. Publicly available datasets and commonly adopted performance evaluation metrics are also …
Continue reading at www.sciencedirect.com (other versions)

Classifications

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    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
    • G06K9/4609—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections by matching or filtering
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    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
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    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
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