most citedPipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science

13 citations · 13 across the 1 of their papers we have counts for

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2 papers

cs.IR2019★ 13 cited

Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science

Huichen Yang, Carlos A. Aguirre, Maria F. De La Torre +10

This paper describes a machine learning and data science pipeline for structured information extraction from documents, implemented as a suite of open-source tools and extensions t…

physics.comp-ph2019

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…