Increase the data acquisition rate of a ghost polarimetry system via deep learning

Application of ghost polarimetry is significantly limited due to the low data acquisition rate. We present the integration of deep learning into a ghost polarimetry to analyze the intensity correlation function and subsequent formation of improved patterns with a modified spectrum of spatial frequen...

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Bibliographic Details
Main Authors: Shumigai, V.S., Moreva, P.E., Tuchin, V.S., Startseva, A.M., Nasedkin, B.A., Tcypkin, A.N.
Format: Conference Proceeding
Language:English
Subjects:
Biology
Correlation
correlation function
Data acquisition
data acquisition rate
Deep learning
ghost polarimetry
Laser applications
Optics
Polarimetry
Online Access:Request full text
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Description
Summary:Application of ghost polarimetry is significantly limited due to the low data acquisition rate. We present the integration of deep learning into a ghost polarimetry to analyze the intensity correlation function and subsequent formation of improved patterns with a modified spectrum of spatial frequencies. Proposed modification makes ghost polarimetry more attractive for biological researches, where the object is often dynamic.
ISSN:2642-5580
DOI:10.1109/ICLO59702.2024.10624566