| Deep learning enabled fault diagnosis using time‐frequency image analysis of rolling element bearings D Verstraete, A Ferrada, EL Droguett, V Meruane, M Modarres Shock and Vibration 2017 (1), 5067651, 2017 | 525 | 2017 |
| Failure and reliability prediction by support vector machines regression of time series data M das Chagas Moura, E Zio, ID Lins, E Droguett Reliability Engineering & System Safety 96 (11), 1527-1534, 2011 | 352 | 2011 |
| Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework T Zhou, T Han, EL Droguett Reliability Engineering & System Safety 224, 108525, 2022 | 248 | 2022 |
| Society for risk analysis glossary T Aven, Y Ben-Haim, HB Andersen, T Cox, EL Droguett, M Greenberg, ... | 221 | 2018 |
| Convolutional neural networks for automated damage recognition and damage type identification C Modarres, N Astorga, EL Droguett, V Meruane Structural Control and Health Monitoring 25 (10), e2230, 2018 | 219 | 2018 |
| Deep variational auto-encoders: A promising tool for dimensionality reduction and ball bearing elements fault diagnosis G San Martin, E Lopez Droguett, V Meruane, M das Chagas Moura Structural Health Monitoring 18 (4), 1092-1128, 2019 | 176 | 2019 |
| Prediction of sea surface temperature in the tropical Atlantic by support vector machines ID Lins, M Araujo, M das Chagas Moura, MA Silva, EL Droguett Computational Statistics & Data Analysis 61, 187-198, 2013 | 149 | 2013 |
| Automatic crack segmentation for UAV-assisted bridge inspection YZ Ayele, M Aliyari, D Griffiths, EL Droguett Energies 13 (23), 6250, 2020 | 144 | 2020 |
| Redundancy allocation problems considering systems with imperfect repairs using multi-objective genetic algorithms and discrete event simulation ID Lins, EL Droguett Simulation Modelling Practice and Theory 19 (1), 362-381, 2011 | 120 | 2011 |
| Bayesian methodology for model uncertainty using model performance data EL Droguett, A Mosleh Risk Analysis: An International Journal 28 (5), 1457-1476, 2008 | 115 | 2008 |
| A particle swarm‐optimized support vector machine for reliability prediction ID Lins, MDC Moura, E Zio, EL Droguett Quality and Reliability Engineering International 28 (2), 141-158, 2012 | 102 | 2012 |
| Integration of deep learning and Bayesian networks for condition and operation risk monitoring of complex engineering systems R Moradi, S Cofre-Martel, EL Droguett, M Modarres, KM Groth Reliability Engineering & System Safety 222, 108433, 2022 | 101 | 2022 |
| Assessment of deep learning techniques for prognosis of solar thermal systems C Correa-Jullian, JM Cardemil, EL Droguett, M Behzad Renewable Energy 145, 2178-2191, 2020 | 98 | 2020 |
| Deep Convolutional Neural Network‐Based Structural Damage Localization and Quantification Using Transmissibility Data S Cofre-Martel, P Kobrich, E Lopez Droguett, V Meruane Shock and Vibration 2019 (1), 9859281, 2019 | 94 | 2019 |
| A probabilistic Bayesian recurrent neural network for remaining useful life prognostics considering epistemic and aleatory uncertainties J Caceres, D Gonzalez, T Zhou, EL Droguett Structural Control and Health Monitoring 28 (10), e2811, 2021 | 89 | 2021 |
| An uncertainty-informed framework for trustworthy fault diagnosis in safety-critical applications T Zhou, L Zhang, T Han, EL Droguett, A Mosleh, FTS Chan Reliability Engineering & System Safety 229, 108865, 2023 | 83 | 2023 |
| NSGA-II-trained neural network approach to the estimation of prediction intervals of scale deposition rate in oil & gas equipment R Ak, Y Li, V Vitelli, E Zio, EL Droguett, CMC Jacinto Expert Systems with Applications 40 (4), 1205-1212, 2013 | 83 | 2013 |
| Organic poultry and eggs capture high price premiums and growing share of specialty markets L Oberholtzer, C Greene, E Lopez US Department of Agriculture, Economic Research Service, 2006 | 83 | 2006 |
| A novel deep capsule neural network for remaining useful life estimation A Ruiz-Tagle Palazuelos, EL Droguett, R Pascual Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2020 | 80 | 2020 |
| Towards interpretable deep learning: a feature selection framework for prognostics and health management using deep neural networks J Figueroa Barraza, E López Droguett, MR Martins Sensors 21 (17), 5888, 2021 | 71 | 2021 |
