Lukas Petrich

Email address

lukas.petrich(at)uni-ulm.de

Phone

+49 (0)731/50-23590

Fax

+49 (0)731/50-23649

Mailing address

 
  • Room no. 1.43
    Helmholtzstr. 18
    D-89069 Ulm
 

Office hours

on appointment

Publications

Heller, L., Karafítová, I., Petrich, L., Pawlas, Z., Shayanfard, P., Beneš, V., Schmidt, V. and Šittner, P.
Numerical microstructure model of NiTi wire reconstructed from 3D-XRD data
Modelling and Simulation in Materials Science and Engineering, 2020, Vol. 28(5), pp. 055007

Kopeček, J., Staněk, J., Habr, S., Seitl, F., Petrich, L., Schmidt, V. and Beneš, V.
Analysis of polycrystalline microstructure of AlMgSc alloy observed by 3D EBSD
Image Analysis & Stereology, 2020, Vol. 39(1), pp. 1-11

Petrich, L., Lohrmann, G., Neumann, M., Martin, F., Frey, A., Stoll, A. and Schmidt, V.
Detection of Colchicum autumnale in drone images, using a machine-learning approach
Precision Agriculture, 2020, Vol. 21, pp. 1291-1303

Seitl, F., Petrich, L., Staněk, J., Krill III, C. E., Schmidt, V. and Beneš, V.
Exploration of Gibbs-Laguerre tessellations for three-dimensional stochastic modeling
Methodology and Computing in Applied Probability, 2020

Furat, O., Wang, M., Neumann, M., Petrich, L., Weber, M., Krill III, C. E. and Schmidt, V.
Machine learning techniques for the segmentation of tomographic image data of functional materials
Frontiers in Materials, 2019, Vol. 6, pp. 145

Král, P., Staněk, J., Kunčická, L., Seitl, F., Petrich, L., Schmidt, V., Beneš, V. and Sklenička, V.
Microstructure changes in HPT-processed copper occurring at room temperature
Materials Characterization, 2019, Vol. 151, pp. 602-611

Petrich, L., Staněk, J., Wang, M., Westhoff, D., Heller, L., Šittner, P., Krill III, C. E., Beneš, V. and Schmidt, V.
Reconstruction of grains in polycrystalline materials from incomplete data using Laguerre tessellation
Microscopy and Microanalysis, 2019, Vol. 25(3), pp. 743-752

Schnepf, A., Huber, K., Landl, M., Meunier, F., Petrich, L. and Schmidt, V.
Statistical characterization of the root system architecture model CRootBox
Vadose Zone Journal, 2018, Vol. 17(1), pp. 170212

Petrich, L., Westhoff, D., Feinauer, J., Finegan, D. P., Daemi, S. R., Shearing, P. R. and Schmidt, V.
Crack detection in lithium-ion cells using machine learning
Computational Materials Science, 2017, Vol. 136, pp. 297-305