Machine learning in scanning transmission electron microscopy
Scanning transmission electron microscopy (STEM) has emerged as a uniquely powerful
tool for structural and functional imaging of materials on the atomic level. Driven by …
tool for structural and functional imaging of materials on the atomic level. Driven by …
Deep learning in electron microscopy
JM Ede - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …
microscopy. This review paper offers a practical perspective aimed at developers with …
Deep learning enabled strain mapping of single-atom defects in two-dimensional transition metal dichalcogenides with sub-picometer precision
Two-dimensional (2D) materials offer an ideal platform to study the strain fields induced by
individual atomic defects, yet challenges associated with radiation damage have so far …
individual atomic defects, yet challenges associated with radiation damage have so far …
A review on CT and X-ray images denoising methods
In medical imaging systems, denoising is one of the important image processing tasks.
Automatic noise removal will improve the quality of diagnosis and requires careful treatment …
Automatic noise removal will improve the quality of diagnosis and requires careful treatment …
A streaming multi-GPU implementation of image simulation algorithms for scanning transmission electron microscopy
Simulation of atomic-resolution image formation in scanning transmission electron
microscopy can require significant computation times using traditional methods. A recently …
microscopy can require significant computation times using traditional methods. A recently …
BM3D image denoising algorithm based on an adaptive filtering
AA Yahya, J Tan, B Su, M Hu, Y Wang, K Liu… - Multimedia Tools and …, 2020 - Springer
Block-matching and 3D filtering algorithm (BM3D) is the current state-of-the-art for image
denoising. This algorithm has a high capacity to achieve better noise removal results as …
denoising. This algorithm has a high capacity to achieve better noise removal results as …
Denoising atomic resolution 4D scanning transmission electron microscopy data with tensor singular value decomposition
Tensor singular value decomposition (SVD) is a method to find a low-dimensional
representation of data with meaningful structure in three or more dimensions. Tensor SVD …
representation of data with meaningful structure in three or more dimensions. Tensor SVD …
Full automation of point defect detection in transition metal dichalcogenides through a dual mode deep learning algorithm
DH Yang, YS Chu, OFN Okello, SY Seo, G Moon… - Materials …, 2024 - pubs.rsc.org
Point defects often appear in two-dimensional (2D) materials and are mostly correlated with
physical phenomena. The direct visualisation of point defects, followed by statistical …
physical phenomena. The direct visualisation of point defects, followed by statistical …
Machine-learning approach for quantified resolvability enhancement of low-dose STEM data
High-resolution electron microscopy is achievable only when a high electron dose is
employed, a practice that may cause damage to the specimen and, in general, affects the …
employed, a practice that may cause damage to the specimen and, in general, affects the …
[HTML][HTML] Oxygen octahedra picker: A software tool to extract quantitative information from STEM images
In perovskite oxide based materials and hetero-structures there are often strong correlations
between oxygen octahedral distortions and functionality. Thus, atomistic understanding of …
between oxygen octahedral distortions and functionality. Thus, atomistic understanding of …