Feature extraction via similarity search: application to atom finding and denoising in electron and scanning probe microscopy imaging.
Suhas SomnathChristopher R SmithSergei V KalininMiaofang ChiAlbina BorisevichNicholas CrossGerd DuscherStephen JessePublished in: Advanced structural and chemical imaging (2018)
We develop an algorithm for feature extraction based on structural similarity and demonstrate its application for atom and pattern finding in high-resolution electron and scanning probe microscopy images. The use of the combined local identifiers formed from an image subset and appended Fourier, or other transform, allows tuning selectivity to specific patterns based on the nature of the recognition task. The proposed algorithm is implemented in Pycroscopy, a community-driven scientific data analysis package, and is accessible through an interactive Jupyter notebook available on GitHub.
Keyphrases
- high resolution
- deep learning
- data analysis
- convolutional neural network
- electron transfer
- electron microscopy
- machine learning
- living cells
- molecular dynamics
- quantum dots
- high speed
- mass spectrometry
- mental health
- healthcare
- solar cells
- single molecule
- tandem mass spectrometry
- neural network
- fluorescent probe
- liquid chromatography