Generative Adversarial Network for Damage Identification in Civil Structures

Surface crack detection using deep learning with shallow CNN architecture for enhanced computation

(2021) Bubryur Kim et al.   NEURAL COMPUTING & APPLICATIONS

Damage‐sensitive feature extraction with stacked autoencoders for unsupervised damage detection

(2021) Moisés Felipe Silva et al.   Structural Control & Health Monitoring

Automated Structural Damage Identification Using Data Normalization and 1-Dimensional Convolutional Neural Network

(2021) Jongbin Won et al.   Applied Sciences-Basel

Detection method of unlearned pattern using support vector machine in damage classification based on deep neural network

(2020) Masayuki Kohiyama et al.   Structural Control & Health Monitoring

Generative adversarial network for road damage detection

(2020) Hiroya Maeda et al.   COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING

Toward data anomaly detection for automated structural health monitoring: Exploiting generative adversarial nets and autoencoders

(2020) Jianxiao Mao et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Unsupervised deep learning approach using a deep auto-encoder with an one-class support vector machine to detect structural damage

(2020) Zilong Wang et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Lost data reconstruction for structural health monitoring using deep convolutional generative adversarial networks

(2020) Xiaoming Lei et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Damage detection in a novel deep-learning framework: a robust method for feature extraction

(2019) Tian Guo et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Damage detection of a cable-stayed bridge using feature extraction and selection methods

(2019) Hossein Babajanian Bisheh et al.   Structure and Infrastructure Engineering

Deep Convolutional Neural Network-Based Structural Damage Localization and Quantification Using Transmissibility Data

(2019) Sergio Cofre-Martel et al.   SHOCK AND VIBRATION

A novel anomaly detection method based on adaptive Mahalanobis-squared distance and one-class kNN rule for structural health monitoring under environmental effects

(2019) Hassan Sarmadi et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A novel unsupervised deep learning model for global and local health condition assessment of structures

(2018) Mohammad Hossein Rafiei et al.   ENGINEERING STRUCTURES

NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion

(2018) Fu-Chen Chen et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

1-D CNNs for structural damage detection: Verification on a structural health monitoring benchmark data

(2018) Osama Abdeljaber et al.   NEUROCOMPUTING

Surface fatigue crack identification in steel box girder of bridges by a deep fusion convolutional neural network based on consumer-grade camera images

(2018) Yang Xu et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Deep principal component analysis: An enhanced approach for structural damage identification

(2018) Moisés Silva et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Data fusion approaches for structural health monitoring and system identification: Past, present, and future

(2018) Rih-Teng Wu et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Damage assessment in structures using combination of a modified Cornwell indicator and genetic algorithm

(2018) S. Tiachacht et al.   ENGINEERING STRUCTURES

Automated Vision-Based Detection of Cracks on Concrete Surfaces Using a Deep Learning Technique

(2018) Byunghyun Kim et al.   SENSORS

Data-driven damage diagnosis under environmental and operational variability by novel statistical pattern recognition methods

(2018) Alireza Entezami et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

A novel deep learning-based method for damage identification of smart building structures

(2018) Yang Yu et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

(2017) Osama Abdeljaber et al.   JOURNAL OF SOUND AND VIBRATION

Evaluation of deep learning approaches based on convolutional neural networks for corrosion detection

(2017) Deegan J Atha et al.   STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL

A novel unsupervised approach based on a genetic algorithm for structural damage detection in bridges

(2016) Moisés Silva et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Stayed-Cable Bridge Damage Detection and Localization Based on Accelerometer Health Monitoring Measurements

(2015) Mosbeh R. Kaloop et al.   SHOCK AND VIBRATION

Signal Processing Techniques for Vibration-Based Health Monitoring of Smart Structures

(2014) Juan Pablo Amezquita-Sanchez et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

Nonlinear multiclass support vector machine–based health monitoring system for buildings employing magnetorheological dampers

(2013) Jo Woon Chong et al.   JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES

SMC structural health monitoring benchmark problem using monitored data from an actual cable-stayed bridge

(2013) Shunlong Li et al.   Structural Control & Health Monitoring

Modal identification of bridges under varying environmental conditions: Temperature and wind effects

(2009) Hui Li et al.   Structural Control & Health Monitoring