most citedClassification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers

3 citations · 3 across the 1 of their papers we have counts for

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cond-mat.mtrl-sci2022★ 3 cited

Classification of FIB/SEM-tomography images for highly porous multiphase materials using random forest classifiers

Markus Osenberg, André Hilger, Matthias Neumann +6

FIB/SEM tomography represents an indispensable tool for the characterization of three-dimensional nanostructures in battery research and many other fields. However, contrast and 3D…