Reconstruction of concrete morphology using deep learning
In this contribution, the concrete morphology is reconstructed with a simple algorithm selecting a pixel value based on the small set of surrounding pixels. A deep neural network (DNN) is used as a classifier, and the authors focus on studying different DNN architectures. The performance of the pro...
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| Format: | Article |
| Language: | English |
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Czech Technical University in Prague
2024-11-01
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| Series: | Acta Polytechnica CTU Proceedings |
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| Online Access: | https://ojs.cvut.cz/ojs/index.php/APP/article/view/10214 |
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| _version_ | 1850057666227863552 |
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| author | Ondřej Šperl Jan Sýkora |
| author_facet | Ondřej Šperl Jan Sýkora |
| author_sort | Ondřej Šperl |
| collection | DOAJ |
| description |
In this contribution, the concrete morphology is reconstructed with a simple algorithm selecting a pixel value based on the small set of surrounding pixels. A deep neural network (DNN) is used as a classifier, and the authors focus on studying different DNN architectures. The performance of the proposed algorithm is evaluated on several statistical descriptors and the grain size distribution
curve.
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| format | Article |
| id | doaj-art-b9844e99cced46fb9bf50101e2c11c59 |
| institution | DOAJ |
| issn | 2336-5382 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Czech Technical University in Prague |
| record_format | Article |
| series | Acta Polytechnica CTU Proceedings |
| spelling | doaj-art-b9844e99cced46fb9bf50101e2c11c592025-08-20T02:51:23ZengCzech Technical University in PragueActa Polytechnica CTU Proceedings2336-53822024-11-014910.14311/APP.2024.49.0085Reconstruction of concrete morphology using deep learningOndřej Šperl0Jan Sýkora1Czech Technical University in Prague, Faculty of Civil Engineering, Department of Mechanics, Thákurova 7, 160 00 Prague, Czech RepublicCzech Technical University in Prague, Faculty of Civil Engineering, Department of Mechanics, Thákurova 7, 160 00 Prague, Czech Republic In this contribution, the concrete morphology is reconstructed with a simple algorithm selecting a pixel value based on the small set of surrounding pixels. A deep neural network (DNN) is used as a classifier, and the authors focus on studying different DNN architectures. The performance of the proposed algorithm is evaluated on several statistical descriptors and the grain size distribution curve. https://ojs.cvut.cz/ojs/index.php/APP/article/view/10214reconstructionconcretedeep learningconvolutional neural network |
| spellingShingle | Ondřej Šperl Jan Sýkora Reconstruction of concrete morphology using deep learning Acta Polytechnica CTU Proceedings reconstruction concrete deep learning convolutional neural network |
| title | Reconstruction of concrete morphology using deep learning |
| title_full | Reconstruction of concrete morphology using deep learning |
| title_fullStr | Reconstruction of concrete morphology using deep learning |
| title_full_unstemmed | Reconstruction of concrete morphology using deep learning |
| title_short | Reconstruction of concrete morphology using deep learning |
| title_sort | reconstruction of concrete morphology using deep learning |
| topic | reconstruction concrete deep learning convolutional neural network |
| url | https://ojs.cvut.cz/ojs/index.php/APP/article/view/10214 |
| work_keys_str_mv | AT ondrejsperl reconstructionofconcretemorphologyusingdeeplearning AT jansykora reconstructionofconcretemorphologyusingdeeplearning |