1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data
暂无分享,去创建一个
Boualem Boashash | Onur Avci | Daniel J. Inman | Osama Abdeljaber | Mustafa Serkan Kiranyaz | Henry Sodano | D. Inman | B. Boashash | Onur Avcı | Osama Abdeljaber | H. Sodano | M. Kiranyaz
[1] Moncef Gabbouj,et al. Personalized Monitoring and Advance Warning System for Cardiac Arrhythmias , 2017, Scientific Reports.
[2] Charles R. Farrar,et al. Machine learning algorithms for damage detection under operational and environmental variability , 2011 .
[3] Chaoqun Hong,et al. Hypergraph regularized autoencoder for image-based 3D human pose recovery , 2016, Signal Process..
[4] Taweh Beysolow. Convolutional Neural Networks (CNNs) , 2017 .
[5] Jun Yu,et al. Multitask Autoencoder Model for Recovering Human Poses , 2018, IEEE Transactions on Industrial Electronics.
[6] Fei-Fei Li,et al. Large-Scale Video Classification with Convolutional Neural Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[7] Onur Avci,et al. Nonparametric structural damage detection algorithm for ambient vibration response: utilizing artificial neural networks and self-organizing maps , 2016 .
[8] Onur Avci,et al. Quantification of Structural Damage with Self-Organizing Maps , 2016 .
[9] James L. Beck,et al. A Bayesian probabilistic approach to structural health monitoring , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).
[10] Xiaodong Gu,et al. Towards dropout training for convolutional neural networks , 2015, Neural Networks.
[11] Jianping Fan,et al. iPrivacy: Image Privacy Protection by Identifying Sensitive Objects via Deep Multi-Task Learning , 2017, IEEE Transactions on Information Forensics and Security.
[12] Michael S. Lew,et al. Deep learning for visual understanding: A review , 2016, Neurocomputing.
[13] Moncef Gabbouj,et al. Convolutional Neural Networks for patient-specific ECG classification , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[14] C.-C. Jay Kuo. Understanding convolutional neural networks with a mathematical model , 2016, J. Vis. Commun. Image Represent..
[15] Mustafa Gul,et al. Structural health monitoring and damage assessment using a novel time series analysis methodology with sensor clustering , 2011 .
[16] C. M. Wen,et al. Unsupervised fuzzy neural networks for damage detection of structures , 2007 .
[17] James L. Beck,et al. A benchmark problem for structural health monitoring , 2001 .
[18] Onur Avci,et al. A Comparative Assessment of Nonlinear State Estimation Methods for Structural Health Monitoring , 2015 .
[19] Shirley J. Dyke,et al. Experimental Phase II of the Structural Health Monitoring Benchmark Problem , 2003 .
[20] Sreenivas Alampalli,et al. Structural identification, damage identification, and structural health monitoring , 2007, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.
[21] Emanuele Zappa,et al. Vision Device Applied to Damage Identification in Civil Engineer Structures , 2014 .
[22] Stefan Wermter,et al. An analysis of Convolutional Long Short-Term Memory Recurrent Neural Networks for gesture recognition , 2017, Neurocomputing.
[23] Abhineet Saxena,et al. Convolutional neural networks: an illustration in TensorFlow , 2016, XRDS.
[24] Moncef Gabbouj,et al. Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks , 2016, IEEE Transactions on Industrial Electronics.
[25] Bijan Samali,et al. Dynamic-Based Damage Identification Using Neural Network Ensembles and Damage Index Method , 2010 .
[26] Moncef Gabbouj,et al. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks , 2017 .
[27] Onur Avci,et al. Iterated square root unscented Kalman filter for nonlinear states and parameters estimation: three DOF damped system , 2015 .
[28] Sven Behnke,et al. Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition , 2010, ICANN.
[29] Charles R. Farrar,et al. Structural Health Monitoring Using Statistical Pattern Recognition Techniques , 2001 .
[30] Keith Worden,et al. An introduction to structural health monitoring , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[31] Onur Avci,et al. Active vibration control of flexible cantilever plates using piezoelectric materials and artificial neural networks , 2016 .
[32] Jochen J. Steil,et al. Modelling of parametrized processes via regression in the model space of neural networks , 2017, Neurocomputing.
[33] Boualem Boashash,et al. Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study , 2016, Knowl. Based Syst..
[34] David Stutz,et al. Understanding Convolutional Neural Networks , 2014 .
[35] Onur Avci,et al. Damage detection using enhanced multivariate statistical process control technique , 2016, 2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA).
[36] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[37] Charles R. Farrar,et al. On Assessing the Robustness of Structural Health Monitoring Technologies , 2012 .
[38] Xue-Feng Zhao,et al. Structure damage diagnosis using neural network and feature fusion , 2011, Eng. Appl. Artif. Intell..
[39] Shao-Fei Jiang,et al. Structural Damage Detection by Integrating Data Fusion and Probabilistic Neural Network , 2006 .
[40] Claudomiro Sales,et al. Machine learning algorithms for damage detection: Kernel-based approaches , 2016 .
[41] Onur Avci,et al. Self-Organizing Maps for Structural Damage Detection: A Novel Unsupervised Vibration-Based Algorithm , 2016 .
[42] John E. T. Penny,et al. Crack Modeling for Structural Health Monitoring , 2002 .
[43] Pang-jo Chun,et al. Bridge Damage Severity Quantification Using Multipoint Acceleration Measurement and Artificial Neural Networks , 2015 .
[44] Yi-Qing Ni,et al. Damage Localization of Cable-Supported Bridges Using Modal Frequency Data and Probabilistic Neural Network , 2014 .
[45] Onur Avci,et al. Structural Damage Detection in Real Time: Implementation of 1D Convolutional Neural Networks for SHM Applications , 2017 .
[46] Viviana Meruane. Online Sequential Extreme Learning Machine for Vibration-Based Damage Assessment Using Transmissibility Data , 2016 .
[47] J M W Brownjohn,et al. Structural health monitoring of civil infrastructure , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[48] Daniel L. Balageas. Introduction to Structural Health Monitoring , 2010 .
[49] Moncef Gabbouj,et al. Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks , 2016, IEEE Transactions on Biomedical Engineering.
[50] F. N. Catbas,et al. Structural health monitoring: applications and data analysis , 2009 .
[51] Chin-Hui Lee,et al. A unified approach to transfer learning of deep neural networks with applications to speaker adaptation in automatic speech recognition , 2016, Neurocomputing.
[52] Jun Yu,et al. Image-Based 3D Human Pose Recovery with Locality Sensitive Sparse Retrieval , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.
[53] Meng Wang,et al. Multimodal Deep Autoencoder for Human Pose Recovery , 2015, IEEE Transactions on Image Processing.