Grain detection from 2d and 3d EBSD data--specification of the MTEX algorithm.
By F. Bachmann, Ralf Hielscher, Helmut Schaeben. Ultramicroscopy, 2011
697 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Environmental Engineering, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/854647a41eca7cc7bdca27dc182f34b47789d4ed
How researchers see this paper
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In Computer Vision and Pattern Recognition
In Environmental Engineering
In Mechanical Engineering
- Dierk Raabe
- Franz Roters
- Philip Eisenlohr
- M. Diehl
- C. Haase
- L. Barrales-Mora
- Duancheng Ma
- Pratheek Shanthraj
Citations in the corpus
- Descriptive tools for the analysis of texture projects with large datasets using MTEX: strength, symmetry and components (2014, background): “…of high-elastic symmetry in seismological analysis has been the motivation for geophysical interest in the decomposition of a general triclinic elastic tensor into components of higher symmetry (e.g. Backus 1970; Harder 1988; Arts et al. 1991; Mainprice & Silver 1993; Browaeys & Chevrot 2004).”
- DAMASK – The Düsseldorf Advanced Material Simulation Kit for modeling multi-physics crystal plasticity, thermal, and damage phenomena from the single crystal up to the component scale (2018, background): “3D [219] or MTEX [345,346]), DAMASK also provides a script with basic functionality for this purpose.”
- Influence of deformation and annealing twinning on the microstructure and texture evolution of face-centered cubic high-entropy alloys (2017, positive): “Subdivision of EBSD mappings into subsets containing only nonrecrystallized (non-RX) or recrystallized (RX) grains was realized using an algorithm of the MATLAB®-based toolbox MTEX [31-33], as described in [34, 35].”