Zobrazeno 1 - 8 of 8 pro vyhledávání: '"Niklas Mevenkamp"'
1
On a hyperbolic conservation law of electron transport in solid materials for electron probe microanalysis
Autor: Manuel Torrilhon, Niklas Mevenkamp, Silvia Richter, Philippe T. Pinard
Publikováno v: Bulletin of the Brazilian Mathematical Society, New Series. 47:575-588
The prediction of X-ray intensities based on the distribution of electrons throughout solid materials is essential to solve the inverse problem of quantifying the composition of materials in electron probe microanalysis (EPMA) [3]. We present a hyper
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c7612ce416dbe327ed4df64c772a4cc4
https://doi.org/10.1007/s00574-016-0170-x
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2
Multi-modal and multi-scale non-local means method to analyze spectroscopic datasets
Autor: Benjamin Berkels, Katherine E. MacArthur, Philipp Ebert, Martial Duchamp, Leslie J. Allen, Vasiliki Tileli, Niklas Mevenkamp
Publikováno v: Ultramicroscopy 209, 112877-(2020). doi:10.1016/j.ultramic.2019.112877
A multi-modal and multi-scale non-local means (M3S-NLM) method is proposed to extract atomically resolved spectroscopic maps from low signal-to-noise (SNR) datasets recorded with a transmission electron microscope. This method improves upon previousl
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d240e21991d3677d951e2501919ed98e
https://doi.org/10.1016/j.ultramic.2019.112877
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4
Variational multi-phase segmentation using high-dimensional local features
Autor: Benjamin Berkels, Niklas Mevenkamp
Publikováno v: 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).
We propose a novel method for multi-phase segmentation of images based on high-dimensional local feature vectors. While the method was developed for the segmentation of extremely noisy crystal images based on localized Fourier transforms, the resulti
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25f8ca58d1586eb3d734cfacf984ef62
https://doi.org/10.1109/wacv.2016.7477729
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6
Poisson noise removal from high-resolution STEM images based on periodic block matching
Autor: Niklas Mevenkamp, Paul M. Voyles, Andrew B. Yankovich, Peter Binev, Wolfgang Dahmen, Benjamin Berkels
Publikováno v: Advanced Structural and Chemical Imaging 1(1), 3 (2015). doi:10.1186/s40679-015-0004-8
Advanced Structural and Chemical Imaging 1(1), 3 (2015). doi:10.1186/s40679-015-0004-8
Published by Springer International Publishing AG, Cham
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a8a0ada4c252d7433a5b6617045c217
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7
Unsupervised and Accurate Extraction of Primitive Unit Cells from Crystal Images
Autor: Benjamin Berkels, Niklas Mevenkamp
Publikováno v: Cham : Springer International Publishing; Springer, Lecture Notes in Computer Science 9358, 105-116 (2015). doi:10.1007/978-3-319-24947-6_9
Pattern Recognition : 37th German Conference, GCPR 2015, Aachen, Germany, October 7–10, 2015, Proceedings / Gall, Juergen [Hrsg.] ; Gehler, Peter [Hrsg.] ; Leibe, Bastian [Hrsg.]
Pattern Recognition : 37th German Conference, GCPR 2015, Aachen, Germany, October 7–10, 2015, Proceedings / Gall, Juergen [Hrsg.] ; Gehler, Peter [Hrsg.] ; Leibe, Bastian [Hrsg.]37. German Conference on Pattern Recognition, GCPR 2015, Aachen, Germany, 2015-10-07-2015-10-09
Lecture Notes in Computer Science ISBN: 9783319249469
GCPR
We present a novel method for the unsupervised estimation of a primitive unit cell, i.e. a unit cell that can’t be further simplified, from a crystal image. Significant peaks of the projective standard deviations of the image serve as candidate lat
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