Search Results - "Cohn, Ryan"

Unsupervised Machine Learning Via Transfer Learning and k-Means Clustering to Classify Materials Image Data by Cohn, Ryan, Holm, Elizabeth

“…Unsupervised machine learning offers significant opportunities for extracting knowledge from unlabeled datasets and for achieving maximum machine learning…”
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Overview: Computer Vision and Machine Learning for Microstructural Characterization and Analysis by Holm, Elizabeth A., Cohn, Ryan, Gao, Nan, Kitahara, Andrew R., Matson, Thomas P., Lei, Bo, Yarasi, Srujana Rao

“…Microstructural characterization and analysis is the foundation of microstructural science, connecting materials structure to composition, process history, and…”
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Recent advances and applications of deep learning methods in materials science by Choudhary, Kamal, DeCost, Brian, Chen, Chi, Jain, Anubhav, Tavazza, Francesca, Cohn, Ryan, Park, Cheol Woo, Choudhary, Alok, Agrawal, Ankit, Billinge, Simon J. L., Holm, Elizabeth, Ong, Shyue Ping, Wolverton, Chris

“…Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based,…”
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Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data by Cohn, Ryan, Anderson, Iver, Prost, Tim, Tiarks, Jordan, White, Emma, Holm, Elizabeth

“…We propose instance segmentation as a useful tool for image analysis in materials science. Instance segmentation is an advanced technique in computer vision…”
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Extreme Abnormal Grain Growth: Connecting Mechanisms to Microstructural Outcomes by Krill, Carl E, Holm, Elizabeth A, Dake, Jules M, Cohn, Ryan, Holíková, Karolína, Andorfer, Fabian

“…If variety is the spice of life, then abnormal grain growth (AGG) may be the materials processing equivalent of sriracha sauce. Abnormally growing grains can…”
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Correction to: Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data by Cohn, Ryan, Anderson, Iver, Prost, Tim, Tiarks, Jordan, White, Emma, Holm, Elizabeth

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Calorimetric Study with Uncertainty Analysis to Investigate the Precipitation Kinetics in a Nanostructured Al Composite by Cohn, Ryan, Fullenwider, Blake, Ma, Kaka, Schoenung, Julie M.

“…Nanostructured Al–Zn–Mg–Cu alloy and boron carbide/Al–Zn–Mg–Cu composite powders are fabricated through cryomilling. η'‐MgZn2 precipitation in each material is…”
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Computer Vision and Deep Learning for Microstructural Modeling and Automated Characterization of Materials by Cohn, Ryan C

“…Deep learning has demonstrated impressive results for a variety of applications in image analysis, but the use of this powerful technique in materials science…”
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Graph convolutional network for predicting abnormal grain growth in Monte Carlo simulations of microstructural evolution by Cohn, Ryan, Holm, Elizabeth

“…Recent developments in graph neural networks show promise for predicting the occurrence of abnormal grain growth, which has been a particularly challenging…”
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Unsupervised machine learning via transfer learning and k-means clustering to classify materials image data by Cohn, Ryan, Holm, Elizabeth

“…Unsupervised machine learning offers significant opportunities for extracting knowledge from unlabeled data sets and for achieving maximum machine learning…”
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Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data by Cohn, Ryan, Anderson, Iver, Prost, Tim, Tiarks, Jordan, White, Emma, Holm, Elizabeth

“…We propose instance segmentation as a useful tool for image analysis in materials science. Instance segmentation is an advanced technique in computer vision…”
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Gaining a Deeper Understanding of Nature with Quantum Simulators and Quantum Computers by Cohn, Jeffrey Ryan

“…Exact simulation of quantum systems is intractable on current classical computers due to the time required to calculate the exponential number of amplitudes…”
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Recent Advances and Applications of Deep Learning Methods in Materials Science by Choudhary, Kamal, DeCost, Brian, Chen, Chi, Jain, Anubhav, Tavazza, Francesca, Cohn, Ryan, WooPark, Cheol, Choudhary, Alok, Agrawal, Ankit, Billinge, Simon J. L, Holm, Elizabeth, Ong, Shyue Ping, Wolverton, Chris

“…Deep learning (DL) is one of the fastest growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based,…”
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Overview: Computer vision and machine learning for microstructural characterization and analysis by Holm, Elizabeth A, Cohn, Ryan, Gao, Nan, Kitahara, Andrew R, Matson, Thomas P, Lei, Bo, Yarasi, Srujana Rao

“…The characterization and analysis of microstructure is the foundation of microstructural science, connecting the materials structure to its composition,…”
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Multiphoton imaging with vibrational contrast and high spatial resolution by Cohn, Keith Ryan

“…Imaging with mid-infrared (mid-IR) radiation is useful for spectroscopic purposes because light of this energy corresponds to vibrational resonances in…”
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Multiphoton imaging with vibrational contrast and high spatial resolution by Cohn, Keith Ryan

“…Imaging with mid-infrared (mid-IR) radiation is useful for spectroscopic purposes because light of this energy corresponds to vibrational resonances in…”
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