Search Results for author: Ayana Ghosh

Found 4 papers, 2 papers with code

AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond

1 code implementation16 May 2021 Maxim Ziatdinov, Ayana Ghosh, Tommy Wong, Sergei V. Kalinin

AtomAI is an open-source software package bridging instrument-specific Python libraries, deep learning, and simulation tools into a single ecosystem.

Disentanglement Ensemble Learning +5

Automated and Autonomous Experiment in Electron and Scanning Probe Microscopy

no code implementations22 Mar 2021 Sergei V. Kalinin, Maxim A. Ziatdinov, Jacob Hinkle, Stephen Jesse, Ayana Ghosh, Kyle P. Kelley, Andrew R. Lupini, Bobby G. Sumpter, Rama K. Vasudevan

Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with domain applications ranging from theory and materials prediction to high-throughput data analysis.

Autonomous Driving Decision Making +1

Ensemble learning and iterative training (ELIT) machine learning: applications towards uncertainty quantification and automated experiment in atom-resolved microscopy

no code implementations21 Jan 2021 Ayana Ghosh, Bobby G. Sumpter, Ondrej Dyck, Sergei V. Kalinin, Maxim Ziatdinov

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.

Ensemble Learning Transfer Learning

Unsupervised Machine Learning Discovery of Chemical and Physical Transformation Pathways from Imaging Data

1 code implementation19 Oct 2020 Sergei V. Kalinin, Ondrej Dyck, Ayana Ghosh, Bobby G. Sumpter, Maxim Ziatdinov

We show that unsupervised machine learning can be used to learn physical and chemical transformation pathways from the observational microscopic data, as demonstrated for atomically resolved images in Scanning Transmission Electron Microscopy (STEM) and ferroelectric domain structures in Piezoresponse Force Microscopy (PFM).

Semantic Segmentation Materials Science

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