Research on Concrete Cracks Recognition based on Dual Convolutional Neural Network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Civil and Structural Engineering
Link
http://link.springer.com/content/pdf/10.1007/s12205-019-2030-x.pdf
Reference22 articles.
1. Abdel-Hamid, O., Mohamed, A. R., Jiang, H., Deng, L., Penn, G., and Yu, D. (2014). “Convolutional neural networks for speech recognition.” IEEE/ACM Transactions on Audio Speech & Language Processing, Vol. 22, No. 10, pp. 1533–1545, DOI: https://doi.org/10.1109/TASLP.2014.2339736 .
2. Abdelqader, I., Abudayyeh, O., and Kelly, M. E. (2003). “Analysis of edge-detection techniques for crack identification in bridges.” Journal of Computing in Civil Engineering, Vol. 17, No. 4, pp. 255–263, DOI: https://doi.org/10.1061/(ASCE)0887-3801(2003)17:4(255) .
3. Cha, Y. J., Choi, W., and Büyüköztürk, O. (2017). “Deep learning-based crack damage detection using convolutional neural networks.” Computer-aided Civil & Infrastructure Engineering, Vol. 32, No. 5, pp. 361–378, DOI: https://doi.org/10.1111/mice.12263 .
4. Fujita, Y., Mitani, Y., and Hamamoto, Y. (2006). “A method for crack detection on a concrete structure.” International Conference on Pattern Recognition, Vol. 3, pp. 901–904, DOI: https://doi.org/10.1109/ICPR.2006.98 .
5. Girshick, R., Donahue, J., Darrell, T., and Malik, J. (2014). “Rich feature hierarchies for accurate object detection and semantic segmentation.” Proc., 2014 IEEE Conference on Computer Vision and Pattern Recognition, IEEE, Columbus, OH, USA, pp. 580–587, DOI: https://doi.org/10.1109/CVPR.2014.81 .
Cited by 14 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. Deep learning-assisted automatic quality assessment of concrete surfaces with cracks and bugholes;Advanced Engineering Informatics;2024-10
2. MultiScaleCrackNet: A parallel multiscale deep CNN architecture for concrete crack classification;Expert Systems with Applications;2024-09
3. Automatic recognition system for concrete cracks with support vector machine based on crack features;Scientific Reports;2024-08-29
4. Concrete Crack Identification Framework Using Optimized Unet and I–V Fusion Algorithm for Infrastructure;KSCE Journal of Civil Engineering;2024-08-07
5. Automatic pixel-level bridge crack detection using learning context flux field with convolutional feature fusion;Journal of Civil Structural Health Monitoring;2024-03-14
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3