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Tracing Hα Fibrils through Bayesian Deep Learning

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 29 Dec 2022Publisher:Zenodo
Authors: Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu; Qin Li; Yan Xu; Jason T. L. Wang; +1 Authors
Code repository: https://github.com/ccsc-tools/FibrilNet/tree/v1.6

doi: 10.5281/zenodo.7516721 , 10.5281/zenodo.7494967 , 10.5281/zenodo.7521568 , 10.5281/zenodo.7492664 , 10.5281/zenodo.7507192 , 10.5281/zenodo.7490676 , 10.5281/zenodo.7490658 , 10.5281/zenodo.7506992

Tracing Hα Fibrils through Bayesian Deep Learning

Abstract

Tracing Hα Fibrils through Bayesian Deep Learning

Related Organizations
Keywords

Tracing Hα, fibril, fibirl, deep learning, Bayesian Deep Learning, magnetogram, Hα Fibrils, Bayesian, deep learninig, solar

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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