Matthias Neumann

发表

Big data for microstructure‐property relationships: A case study of predicting effective conductivities

Volker Schmidt, Ole Stenzel, Omar Pecho, 2017 .

HiKoMat - Material design of hierarchemical storage

John Banhart, André Hilger, Ingo Manke, 2018 .

Machine Learning Techniques for the Segmentation of Tomographic Image Data of Functional Materials

Matthias Weber, Volker Schmidt, Mingyan Wang, 2019, Front. Mater..

Detection of Colchicum autumnale in drone images, using a machine-learning approach

Lukas Petrich, Albert Stoll, Matthias Neumann, 2020, Precision Agriculture.

Simulation eines Zweikoordinatenantriebes unter Nutzung von CAD-Werkzeugen/ Simulation of a two-coordinate drive using CAD tools

Jörg Sorber, Matthias Neumann, Olaf Leier, 1993 .

Asymptotic properties of one-layer artificial neural networks with sparse connectivity

Christian Hirsch, Matthias Neumann, Volker Schmidt, 2021 .

Stochastic 3D modeling of La0.6Sr0.4CoO3−δ cathodes based on structural segmentation of FIB–SEM images

Volker Schmidt, Thomas Hocker, Lorenz Holzer, 2013 .

Predicting Effective Conductivities Based on Geometric Microstructure Characteristics

Volker Schmidt, Ole Stenzel, Omar Pecho, 2016 .

Stochastic 3D modeling of complex three-phase microstructures in SOFC-electrodes with completely connected phases

Volker Schmidt, Omar Pecho, Lorenz Holzer, 2016 .

Hydrostatic Pressure Increases the Catalytic Activity of Amyloid Fibril Enzymes.

Matthias Neumann, Roland Winter, Volker Schmidt, 2016, Angewandte Chemie.