On the use of clustering workflows for automated microstructure segmentation of analytical STEM datasets

Keyphrases

• Scanning Transmission Electron Microscopy 100%
• Microstructure Segmentation 100%
• Manifold Approximation 40%
• Manifold Projection 40%
• 4D Scanning 40%
• Material System 20%
• Composition Change 20%
• Data Combination 20%
• Cohesion 20%
• Variational Autoencoder 20%
• Microscopy Data 20%
• Electron Beam Scanning 20%
• Heusler Alloys 20%
• Matrix Precipitates 20%
• Latent Space 20%
• Energy Dispersive X-ray 20%
• Previous Literature 20%
• Automatic Segmentation 20%
• Unsupervised Clustering 20%
• Structural Composition 20%
• Unsupervised Machine Learning Approach 20%
• Systematic Comparison 20%
• Clustering Metrics 20%
• Al2Cu Precipitates 20%
• Correlated Information 20%
• Co2FeSi 20%

Computer Science

• Approximation (Algorithm) 100%
• Machine Learning Approach 50%
• Unsupervised Clustering 50%
• Variational Autoencoder 50%
• Clustering Metric 50%
• Microscopy Data 50%