Mathias Kersemans

Professor

Universiteit Gent

Belgium

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Mathias Kersemans is a Professor at Universiteit Gent in Belgium. His research focuses on advanced imaging techniques and material characterization, particularly in the areas of nonlinear imaging, neural networks, and thermographic inspection. Recent publications highlight his contributions to the fields of composite materials and ultrasonic characterization, demonstrating innovative approaches to defect detection and material performance assessment.

Mathias Kersemans

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Articles (15)

k-space physics-informed neural network (k-PINN) for compressed spectral mapping and efficient inversion of vibrations in thin composite laminates

Broadband nonlinear RAPID: a baseline-free probabilistic imaging approach for single-defect localization using a sparse sensor network

On the defect detection limits of flash thermography in reflection mode: A comprehensive parametric 3D FE study

Quantitative ultrasonic imaging of weave structure in textile composites

Low-Velocity Impact Resistance and Compression After Impact Strength of Thermoplastic Nanofiber Toughened Carbon/Epoxy Composites with Different Layups

Characterization of the full complex-valued stiffness tensor of orthotropic viscoelastic plates using 3D guided wavefield data

Integrated interval Mahalanobis classification system for the quality classification of turbine blades based on vibrational data incorporating measurement uncertainty

A flexible deep learning framework for thermographic inspection of composites

On the ultrasonic characterization of the stacking sequence of CFRP laminates

Diffusion-compensated correlation analysis of frequency-modulated thermal signal for quantitative infrared thermography

Ultrasonic imaging of damage in plates in spectral ripple frequency domain

Machine learning-based orthotropic stiffness identification using guided wavefield data

An efficient parametrized optical infrared thermography 3D finite element framework for computer vision applications

Enhanced thermographic inspection of woven fabric composites by k-space filtering

Dual-IRT-GAN: A defect-aware deep adversarial network to perform super-resolution tasks in infrared thermographic inspection

Collaborators (6)

Liangliang Cheng

Zheng Fan

N.B. Roozen

Lode Daelemans

Vahid Yaghoubi

Koen Van Den Abeele

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