47 citations · 103 across the 6 of their papers we have counts for
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cs.CV2019★ 47 cited
Efficient Saliency Maps for Explainable AI
T. Nathan Mundhenk, Barry Y. Chen, Gerald Friedland
We describe an explainable AI saliency map method for use with deep convolutional neural networks (CNN) that is much more efficient than popular fine-resolution gradient methods. I…
physics.comp-ph2019★ 47 cited
Predicting Compressive Strength of Consolidated Molecular Solids Using Computer Vision and Deep Learning
Brian Gallagher, Matthew Rever, Donald Loveland +6
We explore the application of computer vision and machine learning (ML) techniques to predict material properties (e.g. compressive strength) based on SEM images. We show that it's…