Volumetric Segmentation via Neural Networks Improves Neutron Crystallography Data Analysis
- DOI
- 10.1109/ccgrid.2019.00070
- Published
- 2019-05
- Container
- 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
- Publisher
- IEEE
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/ccgrid.2019.00070,
title = {Volumetric Segmentation via Neural Networks Improves Neutron Crystallography Data Analysis},
author = {Brendan Sullivan and Rick Archibald and Venu Vandavasi and Patricia Langan and Leighton Coates and Vickie Lynch},
year = {2019},
journal = {2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)},
doi = {10.1109/ccgrid.2019.00070},
url = {https://doi.org/10.1109/ccgrid.2019.00070}
}RIS
TY - JOUR TI - Volumetric Segmentation via Neural Networks Improves Neutron Crystallography Data Analysis AU - Brendan Sullivan AU - Rick Archibald AU - Venu Vandavasi AU - Patricia Langan AU - Leighton Coates AU - Vickie Lynch PY - 2019 JO - 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) DO - 10.1109/ccgrid.2019.00070 UR - https://doi.org/10.1109/ccgrid.2019.00070 ER -
APA
Sullivan, B., Archibald, R., Vandavasi, V., Langan, P., Coates, L., & Lynch, V. (2019). Volumetric Segmentation via Neural Networks Improves Neutron Crystallography Data Analysis. 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). https://doi.org/10.1109/ccgrid.2019.00070
Source records
- crossref · retrieved 2026-09-26T17:40:16.799Z