Rapid and Accurate Identification of Concrete Surface Cracks via a Lightweight & Efficient YOLOv3 Algorithm Article Swipe
Haoan Gu
,
Kai Zhu
,
Alfred Strauß
,
Yehui Shi
,
Dragoslav Šumarac
,
Maosen Cao
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.32604/sdhm.2024.042388
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.32604/sdhm.2024.042388
Concrete materials and structures are extensively used in transformation infrastructure and they usually bear cracks during their long-term operation.Detecting cracks using deep-learning algorithms like YOLOv3 (You Only Look Once version 3) is a new trend to pursue intelligent detection of concrete surface cracks.YOLOv3 is a typical deep-learning algorithm used for object detection.Owing to its generality, YOLOv3 lacks specific efficiency and accuracy in identifying concrete surface cracks.An improved algorithm based on YOLOv3, specialized in the rapid and accurate identification of concrete surface cracks is worthy of investigation.This study proposes a tailored deep-learning algorithm, termed MDN-YOLOv3 (MDN: multi-dilated network), of which the MDN is formulated based on three retrofit techniques, and it provides a new backbone network for YOLOv3.The three specific retrofit techniques are briefed: (i) Depthwise separable convolution is utilized to reduce the size of the backbone network; (ii) The dilated-down sampling structure is proposed and used in the backbone network to achieve multi-scale feature fusion; and (iii) The convolutional block attention module is introduced to enhance feature extraction ability.Results show that the proposed MDN-YOLOv3 is 97.2% smaller and 41.5% faster than YOLOv3 in identifying concrete surface cracks, forming a lightweight & efficient YOLOv3 algorithm for intelligently identifying concrete surface cracks.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.32604/sdhm.2024.042388
- https://www.techscience.com/sdhm/online/detail/20422/pdf
- OA Status
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- Cited By
- 3
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- Related Works
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- OpenAlex ID
- https://openalex.org/W4394926938
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4394926938Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.32604/sdhm.2024.042388Digital Object Identifier
- Title
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Rapid and Accurate Identification of Concrete Surface Cracks via a Lightweight & Efficient YOLOv3 AlgorithmWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
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2024-01-01Full publication date if available
- Authors
-
Haoan Gu, Kai Zhu, Alfred Strauß, Yehui Shi, Dragoslav Šumarac, Maosen CaoList of authors in order
- Landing page
-
https://doi.org/10.32604/sdhm.2024.042388Publisher landing page
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https://www.techscience.com/sdhm/online/detail/20422/pdfDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://www.techscience.com/sdhm/online/detail/20422/pdfDirect OA link when available
- Concepts
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Identification (biology), Computer science, Surface (topology), Algorithm, Mathematics, Geometry, Botany, BiologyTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 2, 2024: 1Per-year citation counts (last 5 years)
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77Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3013156544, https://openalex.org/W3165847323, https://openalex.org/W2921075869, https://openalex.org/W2905163589, https://openalex.org/W2788128679, https://openalex.org/W2941356554, https://openalex.org/W2038492154, https://openalex.org/W2922883380, https://openalex.org/W3037760560, https://openalex.org/W4381615675, https://openalex.org/W2070224912, https://openalex.org/W2020644198, https://openalex.org/W2800346298, https://openalex.org/W2973007446, https://openalex.org/W6767979288, https://openalex.org/W2074287828, https://openalex.org/W2534766417, https://openalex.org/W1972926759, https://openalex.org/W2117552096, https://openalex.org/W2779497038, https://openalex.org/W2128880484, https://openalex.org/W2767213246, https://openalex.org/W1964573040, https://openalex.org/W2000779269, https://openalex.org/W1992462714, https://openalex.org/W2091149439, https://openalex.org/W2137160061, https://openalex.org/W2325975990, https://openalex.org/W2407692387, https://openalex.org/W2586750457, https://openalex.org/W2767522444, https://openalex.org/W3011076052, https://openalex.org/W2886369963, https://openalex.org/W2884786778, https://openalex.org/W6766195037, https://openalex.org/W2980937832, https://openalex.org/W3044248863, https://openalex.org/W4376111741, https://openalex.org/W4224950022, https://openalex.org/W3033645921, https://openalex.org/W2620699831, https://openalex.org/W3014789089, https://openalex.org/W4296120900, https://openalex.org/W2919946988, https://openalex.org/W6631782140, https://openalex.org/W6620707391, https://openalex.org/W3182225701, https://openalex.org/W6628973269, https://openalex.org/W3018816704, https://openalex.org/W6777762140, https://openalex.org/W4311569659, https://openalex.org/W4285238123, https://openalex.org/W6776985292, https://openalex.org/W2972309292, https://openalex.org/W3033272228, https://openalex.org/W3084191006, https://openalex.org/W6762585180, https://openalex.org/W6749781174, https://openalex.org/W6750227808, https://openalex.org/W6731892127, https://openalex.org/W3181806991, https://openalex.org/W3155750399, https://openalex.org/W4220801936, https://openalex.org/W4309175865, https://openalex.org/W3098645781, https://openalex.org/W130013534, https://openalex.org/W3024418937, https://openalex.org/W4293584584, https://openalex.org/W4288020654, https://openalex.org/W4293377385, https://openalex.org/W2977212456, https://openalex.org/W3194700752, https://openalex.org/W2953106684, https://openalex.org/W4394645124, https://openalex.org/W3026882584, https://openalex.org/W4299545679, https://openalex.org/W2796438033 |
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