Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy
Abstract Deep learning has emerged as a technique of choice for rapid feature extraction across imaging disciplines, allowing rapid conversion of the data streams to spatial or spatiotemporal arrays of features of interest. However, applications of deep learning in experimental domains are often lim...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/ec0afdf0559a42ec8e0314cf026fbec6 |
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