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Electron backscatter diffraction (EBSD) has developed over the last few decades into a valuable crystallographic characterisation method for a wide range of sample types. Despite these advances, issues such as the complexity of sample…

Image and Video Processing · Electrical Eng. & Systems 2024-07-17 Zoë Broad , Alex W. Robinson , Jack Wells , Daniel Nicholls , Amirafshar Moshtaghpour , Angus I. Kirkland , Nigel D. Browning

A method is described intended for distributed calibration of a probe microscope scanner consisting in a search for a net of local calibration coefficients (LCCs) in the process of automatic measurement of a standard surface, whereby each…

Materials Science · Physics 2018-12-13 Rostislav V. Lapshin

A new method has been developed for the correction of the distortions and/or enhanced phase differentiation in Electron Backscatter Diffraction (EBSD) data. Using a multi-modal data approach, the method uses segmented images of the phase of…

Data Analysis, Statistics and Probability · Physics 2019-03-11 Marie-Agathe Charpagne , Florian Strub , Tresa M. Pollock

Scanning nanobeam electron diffraction (NBED) with fast pixelated detectors is a valuable technique for rapid, spatially resolved mapping of lattice structure over a wide range of length scales. However, intensity variations caused by…

The intricate fine structure of Kikuchi diffraction plays a vital role in probing phase transformations and strain distributions in functional materials, particularly in electron microscopy. Beyond these applications, it also proves…

Accurately indexing pseudosymmetric materials has long proven challenging for electron backscatter diffraction. The recent emergence of intensity-based indexing approaches promises an enhanced ability to resolve pseudosymmetry compared to…

Materials Science · Physics 2020-09-08 Edward L. Pang , Christopher A. Schuh

High-definition 3D city maps enable city planning and change detection, which is essential for municipal compliance, map maintenance, and asset monitoring, including both built structures and urban greenery. Conventional Digital Surface…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Hezam Albagami , Haitian Wang , Xinyu Wang , Muhammad Ibrahim , Zainy M. Malakan , Abdullah M. Alqamdi , Mohammed H. Alghamdi , Ajmal Mian

SUMMARY Geophysical imaging using the inversion procedure is a powerful tool for the exploration of the Earth's subsurface. However, the interpretation of inverted images can sometimes be difficult, due to the inherent limitations of…

LiDAR-based place recognition is an essential and challenging task both in loop closure detection and global relocalization. We propose Deep Scan Context (DSC), a general and discriminative global descriptor that captures the relationship…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Jiafeng Cui , Tengfei Huang , Yingfeng Cai , Junqiao Zhao , Lu Xiong , Zhuoping Yu

The continuous development of new multiphase alloys with improved mechanical properties requires quantitative microstructure-resolved observation of the nanoscale deformation mechanisms at, e.g., multiphase interfaces. This calls for a…

Accurate grain orientation mapping is essential for understanding and optimizing the performance of polycrystalline materials, particularly in energy-related applications. Lithium nickel oxide (LiNiO$_{2}$) is a promising cathode material…

Disordered Systems and Neural Networks · Physics 2025-11-26 Sebastian Wissel , Jonas Scheunert , Aaron Dextre , Shamail Ahmed , Andreas Bayer , Kerstin Volz , Bai-Xiang Xu

Recent advances in depth sensing technologies allow fast electronic maneuvering of the laser beam, as opposed to fixed mechanical rotations. This will enable future sensors, in principle, to vary in real-time the sampling pattern. We…

Computer Vision and Pattern Recognition · Computer Science 2022-05-23 Ilya Tcenov , Guy Gilboa

Electron diffraction through a thin patterned silicon membrane can be used to create complex spatial modulations in electron distributions by varying the intensity of different reflections using parameters such as crystallographic…

Accelerator Physics · Physics 2019-05-30 L. E. Malin , W. S. Graves , M. Holl , J. C. H. Spence , E. A. Nanni , R. K. Li , X. Shen , S. Weathersby

A method is described intended for distributed calibration of a probe microscope scanner consisting in a search for a net of local calibration coefficients (LCCs) in the process of automatic measurement of a standard surface, whereby each…

Materials Science · Physics 2015-11-24 Rostislav V. Lapshin

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as…

Quantitative interpretation of transmission electron microscopy (TEM) data of crystalline specimens often requires the accurate knowledge of the local crystal orientation. A method is presented which exploits momentum-resolved scanning TEM…

Reconstructing materials in the real world has always been a difficult problem in computer graphics. Accurately reconstructing the material in the real world is critical in the field of realistic rendering. Traditionally, materials in…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Zhiyao Luo , Hongnan Chen

Resolving pseudosymmetry has long presented a challenge for electron backscatter diffraction (EBSD) and has been notoriously challenging in the case of tetragonal ZrO2 in particular. In this work, a method is proposed to resolve…

Materials Science · Physics 2020-03-11 Edward L. Pang , Peter M. Larsen , Christopher A. Schuh

The use of highly sensitive pixelated direct detectors has dramatically improved the performance of high energy instrumentation such as transmission electron microscopy. Here, we describe a recently developed monolithic active pixel sensor…

Local learning of sparse image models has proven to be very effective to solve inverse problems in many computer vision applications. To learn such models, the data samples are often clustered using the K-means algorithm with the Euclidean…

Computer Vision and Pattern Recognition · Computer Science 2016-04-20 Julio Cesar Ferreira , Elif Vural , Christine Guillemot