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CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures
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| Published in: | Applied Computer Systems |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1867301673879207937 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | Applied Computer Systems |
| description | |
| discipline_display | Computer Science |
| discipline_facet | Computer Science |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:77939 |
| institution | FRELIP |
| journal_source_facet | Applied Computer Systems |
| publishDate | 2025 |
| publishDateSort | 2025 |
| record_format | rss_article |
| spellingShingle | CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures Computer Science General Computer Science |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Computer Science General Computer Science Computer Science General Computer Science |
| subject_facet | Computer Science General Computer Science |
| title | CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures |
| title_auth | CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures |
| title_full | CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures |
| title_fullStr | CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures |
| title_full_unstemmed | CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures |
| title_short | CrackNet-VGG: A Deep Learning Framework for Automated Detection of Surface Cracks in Concrete Structures |
| title_sort | cracknet-vgg: a deep learning framework for automated detection of surface cracks in concrete structures |
| topic | Computer Science General Computer Science |
| url | https://sciendo.com/article/10.2478/acss-2025-0020 |