A brief introductory review to deep generative models for civil structural health monitoring

F Luleci, FN Catbas - AI in Civil Engineering, 2023 - Springer
The use of deep generative models (DGMs) such as variational autoencoders,
autoregressive models, flow-based models, energy-based models, generative adversarial …

CycleGAN for undamaged-to-damaged domain translation for structural health monitoring and damage detection

F Luleci, FN Catbas, O Avci - Mechanical Systems and Signal Processing, 2023 - Elsevier
The advances in data science in the last few decades have benefitted many other fields,
including Structural Health Monitoring (SHM). Artificial Intelligence (AI), such as Machine …

Improved undamaged-to-damaged acceleration response translation for Structural Health Monitoring

F Luleci, O Avci, FN Catbas - Engineering Applications of Artificial …, 2023 - Elsevier
Unpaired image-to-image translation is a popular research topic in computer vision and
graphics. Recently, the authors of this paper took a similar approach and translated the …

On the Generation of Digital Data and Models from Point Clouds: Application to a Pedestrian Bridge Structure

FN Catbas, JA Cano, F Luleci, LC Walters… - Infrastructures, 2023 - mdpi.com
This study investigates the capture of digital data and the development of models for
structures with incomplete documentation and plans. LiDAR technology is utilized to obtain …

Condition transfer between prestressed bridges using structural state translation for structural health monitoring

F Luleci, F Necati Catbas - AI in Civil Engineering, 2023 - Springer
Abstract Implementing Structural Health Monitoring (SHM) systems with extensive sensing
layouts on all civil structures is obviously expensive and unfeasible. Thus, estimating the …