Martin Takáč
- DynNet: Physics-based neural architecture design for nonlinear structural response modeling and prediction. In: Engineering Structures, v. 229 (Februar 2021). (2021):
- Uncertainty quantification in digital image correlation for experimental evaluation of deep learning based damage diagnostic. In: Structure and Infrastructure Engineering, v. 17, n. 11 (September 2021). (2021):
- Structural sensing with deep learning: Strain estimation from acceleration data for fatigue assessment. In: Computer-Aided Civil and Infrastructure Engineering, v. 35, n. 12 (12 November 2020). (2020):
- Modal Identification of Bridges Using Mobile Sensors with Sparse Vibration Data. In: Journal of Engineering Mechanics (ASCE), v. 146, n. 4 (April 2020). (2020):
- Convolutional Neural Network Approach for Robust Structural Damage Detection and Localization. In: Journal of Computing in Civil Engineering, v. 33, n. 3 (Mai 2019). (2019):