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Gated Dense Convolutional Neural Networks for Unbalanced Representations in STEM Tomography

Published online by Cambridge University Press:  22 July 2022

Arda Genc ,
Libor Kovarik  and
Hamish L. Fraser
Arda Genc*
Affiliation:
 Center for the Accelerated Maturation of Materials, Department of Materials Science and Engineering, The Ohio State University, Columbus, OH, USA
Libor Kovarik
Affiliation:
 Institute for Integrated Catalysis, Pacific Northwest National Laboratory, Richland, WA, USA
Hamish L. Fraser
Affiliation:
 Center for the Accelerated Maturation of Materials, Department of Materials Science and Engineering, The Ohio State University, Columbus, OH, USA
*
*Corresponding author: genc.2@osu.edu

Abstract

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Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 3136 - 3137
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Copyright
Copyright © Microscopy Society of America 2022

References

Ronneberger, O., Fischer, P., Brox, T., U-Net: Convolutional Networks for Biomedical Image Segmentation, In International Conference on Medical Image Computing and Computer-Assisted Intervention, 9351 (2015) 234-241.Google Scholar
Vaswani, A., et al. , Attention is All You Need, arXiv 1706.03762v5 (2017).Google Scholar
Genc, A., Kovarik, L., Fraser, H.L., arXiv 2201.07342v1 (2021).Google Scholar
Oktay, O. et al. , Attention U-Net: Learning Where to Look for the Pancreas, arXiv 1804.03999v3 (2018).Google Scholar