Classification of defects in wooden structures using pre-trained models of convolutional neural network-Reference-Cited by-同舟云学术

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Classification of defects in wooden structures using pre-trained models of convolutional neural network

Published:2023-12 Issue: Volume:19 Page:e02530
ISSN:2214-5095
Container-title:Case Studies in Construction Materials
language:en
Short-container-title:Case Studies in Construction Materials

Author:

Ehtisham Rana,Qayyum Waqas,Camp Charles V.,Plevris Vagelis^ORCID,Mir Junaid,Khan Qaiser-uz Zaman,Ahmad Afaq

Funder

Qatar National Library

Commission on Higher Education

Publisher

Elsevier BV

Subject

Materials Science (miscellaneous)

Reference66 articles.

1. Magnière, N., S. Franke, B. Franke, Investigation on elements presenting cracks in timber structures, in World Conference on Timber Engineering (WCTE 2014). 2014: Quebec, Canada.

2. Wood defects classification using laws texture energy measures and supervised learning approach;Kamal;Adv. Eng. Inform.,2017

3. Mergny, E., R. Mateo, M. Esteban, T. Descamps, and P. Latteur, Influence of cracks on the stiffness of timber structural elements, in World Conference on Timber Engineering (WCTE 2016). 2016: Vienna, Austria.

4. Artificial Intelligence (AI) Applied in Civil Engineering;Lagaros;Appl. Sci.,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Computing the characteristics of defects in wooden structures using image processing and CNN;Automation in Construction;2024-02

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