- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
Identification of new particle formation events with deep learning ; volume:18 ; number:13 ; year:2018 ; pages:9597-9615
Atmospheric chemistry and physics ; 18, Heft 13 (2018), 9597-9615
- Creator
-
Joutsensaari, Jorma
Ozon, Matthew
Nieminen, Tuomo
Mikkonen, Santtu
Lähivaara, Timo
Decesari, Stefano
Facchini, M. Cristina
Laaksonen, Ari
Lehtinen, Kari E. J.
- DOI
-
10.5194/acp-18-9597-2018
- URN
-
urn:nbn:de:101:1-2018071204314281474345
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:21 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Joutsensaari, Jorma
- Ozon, Matthew
- Nieminen, Tuomo
- Mikkonen, Santtu
- Lähivaara, Timo
- Decesari, Stefano
- Facchini, M. Cristina
- Laaksonen, Ari
- Lehtinen, Kari E. J.
Other Objects (12)
New Particle Formation Events Detection with Deep Learning
Nocturnal new particle formation events in urban environments
Identification and quantification of particle growth channels during new particle formation
New particle formation event detection with Mask R-CNN
New Particle Formation Events Observed during the COALA-2020 Campaign
Kinetic nucleation and ions in boreal forest particle formation events
Particle hygroscopicity during atmospheric new particle formation events: implications for the chemical species contributing to particle growth
Differentiating between particle formation and growth events in an urban environment
Ambient new particle formation parameter indicates potential rise in future events
Vertical and horizontal distribution of regional new particle formation events in Madrid
Pileup per particle identification
Particle Identification in Jets and High-Multiplicity pp Events with the ALICE TPC
New Particle Formation Events Detection with Deep Learning
Nocturnal new particle formation events in urban environments
Identification and quantification of particle growth channels during new particle formation
New particle formation event detection with Mask R-CNN
New Particle Formation Events Observed during the COALA-2020 Campaign
Kinetic nucleation and ions in boreal forest particle formation events
Particle hygroscopicity during atmospheric new particle formation events: implications for the chemical species contributing to particle growth
Differentiating between particle formation and growth events in an urban environment
Ambient new particle formation parameter indicates potential rise in future events
Vertical and horizontal distribution of regional new particle formation events in Madrid
Pileup per particle identification
Particle Identification in Jets and High-Multiplicity pp Events with the ALICE TPC
New Particle Formation Events Detection with Deep Learning
Nocturnal new particle formation events in urban environments
Identification and quantification of particle growth channels during new particle formation
New particle formation event detection with Mask R-CNN
New Particle Formation Events Observed during the COALA-2020 Campaign
Kinetic nucleation and ions in boreal forest particle formation events
Particle hygroscopicity during atmospheric new particle formation events: implications for the chemical species contributing to particle growth
Differentiating between particle formation and growth events in an urban environment
Ambient new particle formation parameter indicates potential rise in future events
Vertical and horizontal distribution of regional new particle formation events in Madrid
Pileup per particle identification