Attribution-Driven Explanation of the Deep Neural Network Model via Conditional Microstructure Image Synthesis.
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ABSTRACT:
SUBMITTER: Liu S
PROVIDER: S-EPMC8793074 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature
Publications
Attribution-Driven Explanation of the Deep Neural Network Model via Conditional Microstructure Image Synthesis.
Liu Shusen S Kailkhura Bhavya B Zhang Jize J Hiszpanski Anna M AM Robertson Emily E Loveland Donald D Zhong Xiaoting X Han T Yong-Jin TY
ACS omega 20220107 3
The materials science community has been increasingly interested in harnessing the power of deep learning to solve various domain challenges. However, despite their effectiveness in building highly predictive models, e.g., predicting material properties from microstructure imaging, due to their opaque nature fundamental challenges exist in extracting meaningful domain knowledge from the deep neural networks. In this work, we propose a technique for interpreting the behavior of deep learning mode ...[more]
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