Studying Cracks in Infrastructures Using Amalgamation of AlexNet and Moth Flame Optimizer-Reference-Cited by-同舟云学术

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Studying Cracks in Infrastructures Using Amalgamation of AlexNet and Moth Flame Optimizer

Published:2021-12-07 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Decision Aid Sciences and Application (DASA)
language:
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Author:

Abdelkader Eslam Mohammed¹,Al-Sakkaf Abobakr²,Alfalah Ghasan³

Affiliation:

1. Cairo University,Faculty of Engineering,Structural Engineering Department,Giza,Egypt

2. Concordia University,Department of Building, Civil and Environmental Engineering,Montreal,Canada

3. King Saud University,Department of Architecture & Building Sciences,Riyadh,Saudi Arabia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9681917/9681918/09682310.pdf?arnumber=9682310

Reference37 articles.

1. ImageNet Classification with Deep Convolutional Neural Networks;krizhevsky;Advances in neural information processing systems,2012

2. Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm

3. Automatic Bridge Crack Detection Using a Convolutional Neural Network

4. SDNET2018: An annotated image dataset for non-contact concrete crack detection using deep convolutional neural networks

5. An Adaptive Structural Learning of Deep Belief Network for Image-based Crack Detection in Concrete Structures Using SDNET2018

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. Cracks segmentation of engineering structures in complex backgrounds using a concatenation of Transformer and CNN models driven by scene understanding information;Structures;2024-07

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