Comparative of machine learning classification strategies for electron energy loss spectroscopy: Support vector machines and artificial neural networks

Phase Object Reconstruction for 4D-STEM using Deep Learning

(2023) Thomas Friedrich et al.   MICROSCOPY AND MICROANALYSIS

TEMImageNet training library and AtomSegNet deep-learning models for high-precision atom segmentation, localization, denoising, and deblurring of atomic-resolution images

(2021) Ruoqian Lin et al.   Scientific Reports

Probing atomic-scale symmetry breaking by rotationally invariant machine learning of multidimensional electron scattering

(2021) Mark P. Oxley et al.   npj Computational Materials

A deep learning based automatic defect analysis framework for In-situ TEM ion irradiations

(2021) Mingren Shen et al.   COMPUTATIONAL MATERIALS SCIENCE

Hierarchically Structured Classification of Carbon Nanostructures from TEM Images by Machine Learning and Computer Vision

(2021) Chen Wang et al.   MICROSCOPY AND MICROANALYSIS

Direct Evidence of a Graded Magnetic Interface in Bimagnetic Core/Shell Nanoparticles Using Electron Magnetic Circular Dichroism (EMCD)

(2021) Daniel del-Pozo-Bueno et al.   NANO LETTERS

Defect Detection in Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning

(2021) Philip Cho et al.   Mathematics

Strategies for EELS Data Analysis. Introducing UMAP and HDBSCAN for Dimensionality Reduction and Clustering

(2021) Javier Blanco-Portals et al.   MICROSCOPY AND MICROANALYSIS

Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning

(2021) Andreas Leitherer et al.   Nature Communications

RapidEELS: machine learning for denoising and classification in rapid acquisition electron energy loss spectroscopy

(2021) Cassandra M. Pate et al.   Scientific Reports

Statistically Representative Metrology of Nanoparticles via Unsupervised Machine Learning of TEM Images

(2021) Haotian Wen et al.   Nanomaterials

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

(2021) Sarah Akers et al.   npj Computational Materials

Support vector machine for EELS oxidation state determination

(2020) D. del-Pozo-Bueno et al.   ULTRAMICROSCOPY

Towards calibration-invariant spectroscopy using deep learning

(2019) M. Chatzidakis et al.   Scientific Reports

Precise Size Control of the Growth of Fe3O4 Nanocubes over a Wide Size Range Using a Rationally Designed One-Pot Synthesis

(2019) Javier Muro-Cruces et al.   ACS Nano

Building ferroelectric from the bottom up: The machine learning analysis of the atomic-scale ferroelectric distortions

(2019) M. Ziatdinov et al.   APPLIED PHYSICS LETTERS

Machine Learning for Challenging EELS and EDS Spectral Decomposition

(2019) Thomas Blum et al.   MICROSCOPY AND MICROANALYSIS

The evolution of precipitate crystal structures in an Al-Mg-Si(-Cu) alloy studied by a combined HAADF-STEM and SPED approach

(2018) J.K. Sunde et al.   MATERIALS CHARACTERIZATION

Clustering analysis strategies for electron energy loss spectroscopy (EELS)

(2018) Pau Torruella et al.   ULTRAMICROSCOPY

Spin canting across core/shell Fe3O4/MnxFe3−xO4 nanoparticles

(2018) Samuel D. Oberdick et al.   Scientific Reports

Crystal Phase Mapping by Scanning Precession Electron Diffraction and Machine Learning Decomposition

(2018) Håkon W. Ånes et al.   MICROSCOPY AND MICROANALYSIS

Manifold learning of four-dimensional scanning transmission electron microscopy

(2018) Xin Li et al.   npj Computational Materials

Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning

(2017) Jeff Heaton   Genetic Programming and Evolvable Machines

Electron energy-loss spectroscopic tomography of FexCo(3−x)O4 impregnated Co3O4 mesoporous particles: unraveling the chemical information in three dimensions

(2016) L. Yedra et al.   ANALYST

3D Visualization of the Iron Oxidation State in FeO/Fe3O4 Core–Shell Nanocubes from Electron Energy Loss Tomography

(2016) Pau Torruella et al.   NANO LETTERS

Deep learning

(2015) Yann LeCun et al.   NATURE

Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection

(2015) Ricardo J. G. B. Campello et al.   ACM Transactions on Knowledge Discovery from Data

Retrieving the electronic properties of silicon nanocrystals embedded in a dielectric matrix by low-loss EELS

(2014) Alberto Eljarrat et al.   Nanoscale

Representation Learning: A Review and New Perspectives

(2013) Y. Bengio et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Spectral mixture analysis of EELS spectrum-images

(2012) Nicolas Dobigeon et al.   ULTRAMICROSCOPY

Oxidation state and chemical shift investigation in transition metal oxides by EELS

(2012) Haiyan Tan et al.   ULTRAMICROSCOPY

EEL spectroscopic tomography: Towards a new dimension in nanomaterials analysis

(2012) Lluís Yedra et al.   ULTRAMICROSCOPY

Statistical consequences of applying a PCA noise filter on EELS spectrum images

(2012) Stijn Lichtert et al.   ULTRAMICROSCOPY

A modified possibilistic fuzzy c-means clustering algorithm for bias field estimation and segmentation of brain MR image

(2011) Ze-Xuan Ji et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Mapping titanium and tin oxide phases using EELS: An application of independent component analysis

(2010) F. de la Peña et al.   ULTRAMICROSCOPY

Atomic-resolution imaging of oxidation states in manganites

(2009) M. Varela et al.   PHYSICAL REVIEW B

Multivariate statistical analysis of electron energy-loss spectroscopy in anisotropic materials

(2007) Xuerang Hu et al.   ULTRAMICROSCOPY