Classification of Ice Crystal Habits Observed From Airborne Cloud Particle Imager by Deep Transfer Learning

Classification of Ice Crystal Habits Observed From Airborne Cloud Particle Imager by Deep Transfer Learning

Abstract Ice clouds are mostly composed of different ice crystal habits. It is of great importance to classify ice crystal habits seeing as they could greatly impact single‐scattering properties of ice crystal particles. The single‐scattering properties play an important role in the study of cloud r...

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Bibliographic Details
Main Authors: Haixia Xiao, Feng Zhang, Qianshan He, Pu Liu, Fei Yan, Lijuan Miao, Zhipeng Yang
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2019-10-01
Series:Earth and Space Science
Subjects:
classification
ice crystals
deep convolutional neural network
ice clouds
transfer learning
Online Access:https://doi.org/10.1029/2019EA000636

Internet

https://doi.org/10.1029/2019EA000636

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