A machine learning approach to aerosol classification for single-particle mass spectrometry
- DOI
- 10.5194/amt-11-5687-2018
- Published
- 2018-10-18
- Container
- Atmospheric Measurement Techniques
- Publisher
- Copernicus GmbH
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.5194/amt-11-5687-2018,
title = {A machine learning approach to aerosol classification for single-particle mass spectrometry},
author = {Costa D. Christopoulos and Sarvesh Garimella and Maria A. Zawadowicz and Ottmar Möhler and Daniel J. Cziczo},
year = {2018},
journal = {Atmospheric Measurement Techniques},
doi = {10.5194/amt-11-5687-2018},
url = {https://doi.org/10.5194/amt-11-5687-2018}
}RIS
TY - JOUR TI - A machine learning approach to aerosol classification for single-particle mass spectrometry AU - Costa D. Christopoulos AU - Sarvesh Garimella AU - Maria A. Zawadowicz AU - Ottmar Möhler AU - Daniel J. Cziczo PY - 2018 JO - Atmospheric Measurement Techniques DO - 10.5194/amt-11-5687-2018 UR - https://doi.org/10.5194/amt-11-5687-2018 ER -
APA
Christopoulos, C. D., Garimella, S., Zawadowicz, M. A., Möhler, O., & Cziczo, D. J. (2018). A machine learning approach to aerosol classification for single-particle mass spectrometry. Atmospheric Measurement Techniques. https://doi.org/10.5194/amt-11-5687-2018
Source records
- crossref · retrieved 2026-09-26T05:04:11.325Z