65 citations · 163 across the 12 of their papers we have counts for
12 papers
A Neural Network Enhanced Born Approximation for Inverse Scattering
Ansh Desai, Jonathan Ma, Timo Lahivaara +1
Time-harmonic acoustic inverse scattering concerns the ill-posed and nonlinear problem of determining the refractive index of an inaccessible, penetrable scatterer based on far fie…
Simultaneous estimation of electrical conductivity and permittivity in quantitative thermoacoustic tomography
Teemu Sahlström, Timo Lähivaara, Tanja Tarvainen
In this work, the inverse problem of quantitative thermoacoustic tomography is studied. In quantitative thermoacoustic tomography, dielectric parameters of an imaged target are est…
Monitoring of water volume in a porous reservoir using seismic data: Validation of a numerical model with a field experiment
Mahnaz Khalili, Bojan Brodic, Peter Göransson +6
As global groundwater levels continue to decline rapidly, there is a growing need for advanced techniques to monitor and manage aquifers effectively. This study focuses on validati…
A High-Order Ultra-Weak Variational Formulation for Electromagnetic Waves Utilizing Curved Elements
Timo Lähivaara, William F. Hall, Matti Malinen +3
The Ultra Weak Variational Formulation (UWVF) is a special Trefftz discontinuous Galerkin method, here applied to the time-harmonic Maxwell's equations. The method uses superpositi…
The Time Domain Linear Sampling Method for determining the shape of multiple scatterers using electromagnetic waves
Timo Lähivaara, Peter Monk, Virginia Selgas
The time domain linear sampling method (TD-LSM) solves inverse scattering problems using time domain data by creating an indicator function for the support of the unknown scatterer…
Model reduction in acoustic inversion by artificial neural network
Janne Koponen, Timo Lähivaara, Jari Kaipio +1
In ultrasound tomography, the speed of sound inside an object is estimated based on acoustic measurements carried out by sensors surrounding the object. An accurate forward model i…
Estimation of moisture content distribution in porous foam using microwave tomography with neural networks
Timo Lähivaara, Rahul Yadav, Guido Link +1
The use of microwave tomography (MWT) in an industrial drying process is demonstrated in this feasibility study with synthetic measurement data. The studied imaging modality is app…
A Discontinuous Galerkin method for three-dimensional elastic and poroelastic wave propagation: forward and adjoint problems
Nick Dudley Ward, Simon Eveson, Timo Lahivaara
We develop a numerical solver for three-dimensional wave propagation in coupled poroelastic-elastic media, based on a high-order discontinuous Galerkin (DG) method, with the Biot p…
A Bayesian-based approach to improving acoustic Born waveform inversion of seismic data for viscoelastic media
Kenneth Muhumuza, Lassi Roininen, Janne M. J. Huttunen +1
In seismic waveform inversion, the reconstruction of the subsurface properties is usually carried out using approximative wave propagation models to ensure computational efficiency…
Gaussian process regression for forest attribute estimation from airborne laser scanning data
Petri Varvia, Timo Lähivaara, Matti Maltamo +2
While the analysis of airborne laser scanning (ALS) data often provides reliable estimates for certain forest stand attributes -- such as total volume or basal area -- there is sti…
Estimation of groundwater storage from seismic data using deep learning
Timo Lähivaara, Alireza Malehmir, Antti Pasanen +3
Convolutional neural networks can provide a potential framework to characterize groundwater storage from seismic data. Estimation of key components such as the amount of groundwate…
Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography
Timo Lähivaara, Leo Kärkkäinen, Janne M. J. Huttunen +1
We study the feasibility of data based machine learning applied to ultrasound tomography to estimate water-saturated porous material parameters. In this work, the data to train the…