| A comparison of model selection methods for compressive strength prediction of high-performance concrete using neural networks M Slonski Computers & Structures 88 (21-22), 1248-1253, 2010 | 89 | 2010 |
| Detection of Flaws in Concrete Using Ultrasonic Tomography and Convolutional Neural Networks M Słoński, K Schabowicz, E Krawczyk Materials 13 (7), 1557, 2020 | 46 | 2020 |
| Selected problem of artificial neural networks development Z Waszczyszyn, M Słoński Advances of Soft Computing in Engineering, CISM International Centre for …, 2010 | 33* | 2010 |
| Application of the Gaussian process for fatigue life prediction under multiaxial loading A Karolczuk, M Słoński Mechanical Systems and Signal Processing 167, 108599, 2022 | 31 | 2022 |
| A comparison of deep convolutional neural networks for image-based detection of concrete surface cracks M Słoński Computer Assisted Methods in Engineering and Science 26 (2), 105-112, 2019 | 27 | 2019 |
| 2D Digital Image Correlation and Region-Based Convolutional Neural Network in Monitoring and Evaluation of Surface Cracks in Concrete Structural Elements M Słoński, M Tekieli Materials 13 (16), 3527, 2020 | 25 | 2020 |
| Flexible Adhesive in Composite-to-Brick Strengthening—Experimental and Numerical Study A Kwiecień, P Krajewski, Ł Hojdys, M Tekieli, M Słoński Polymers 10 (4), 356, 2018 | 25 | 2018 |
| Bayesian neural networks and gaussian processes in identification of concrete properties M Słoński Computer Assisted Mechanics and Engineering Sciences 18, 291-302, 2011 | 20* | 2011 |
| Gaussian mixture model for time series-based structural damage detection M Słoński Computer Assisted Methods in Engineering and Science 19, 331-338, 2012 | 13* | 2012 |
| Computer vision based method for real time material and structure parameters estimation using digital image correlation, particle filtering and finite element method M Tekieli, M Słoński Artificial Intelligence and Soft Computing 7894, 624-633, 2013 | 10 | 2013 |
| Maximum of Marginal Likelihood Criterion instead of Cross-Validation for Designing of Artificial Neural Networks Z Waszczyszyn, M Słoński Artificial Intelligence and Soft Computing - ICAISC 2008, 186-194, 2008 | 8 | 2008 |
| Digital image correlation and Bayesian filtering in inverse analysis of structures M Tekieli, M Słoński Recent advances in civil engineering: computational methods 481, 111-124, 2015 | 7 | 2015 |
| Particle filtering for computer vision-based identification of frame model parameters M Tekieli, M Słoński Computer Assisted Methods in Engineering and Science 21, 39-48, 2014 | 7 | 2014 |
| HPC strength prediction using Bayesian neural networks M Słoński Computer Assisted Mechanics and Engineering Sciences 14, 345-352, 2007 | 7 | 2007 |
| Application of Monte Carlo filter for computer vision-based Bayesian updating of finite element model M Tekieli, M Słoński Mechanics and Control 33, 171-177, 2013 | 6 | 2013 |
| Prediction of concrete fatigue durability using Bayesian neural networks M Słoński Computer Assisted Mechanics and Engineering Sciences 12, 259-265, 2005 | 6 | 2005 |
| Bayesian regression approaches on example of concrete fatigue failure prediction M Słoński Computer Assisted Mechanics and Engineering Sciences 13, 655-668, 2006 | 5 | 2006 |
| Bayesian neural networks for prediction of response spectra Z Waszczyszyn, M Słoński Foundations of Civil and Environmental Engineering 7, 343-361, 2006 | 5 | 2006 |
| Analysis of Some Problems of Experimental Mechanics and Biomechanics by Means the ANFIS Neuro-Fuzzy System Z Waszczyszyn, M Slonski Journal of Theoretical and Applied Mechanics 38 (2), 429-446, 2000 | 5 | 2000 |
| Some New Results And Prospect Of Neural Analysis Of Building Vibration Problems Z Waszczyszyn, K Kuzniar, R Obiała, M Słonski Engineering Applications of Neural Networks,’’ed. W. Duch, Wydawnictwo Adam …, 1999 | 5 | 1999 |
Marcin TekieliCracow University of TechnologyZweryfikowany adres z l5.pk.edu.pl
