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Conference Paper: Automatic Detection of Microplastics by Deep Learning Enabled Digital Holography

TitleAutomatic Detection of Microplastics by Deep Learning Enabled Digital Holography
Authors
Issue Date2020
PublisherOptical Society of America.
Citation
Digital Holography and Three-Dimensional Imaging Meeting in Imaging and Applied Optics Congress, Washington, DC, USA, 22–26 June 2020, paper HTu5B.1 How to Cite?
AbstractAn inline digital holography with deep learning is developed to detect microplastics automatically from the raw holograms, without any additional image processing and analysis.
DescriptionSession: Learning-based Approaches in Digital Holography II (HTu5B) - paper HTu5B.1
Persistent Identifierhttp://hdl.handle.net/10722/290715
ISBN

 

DC FieldValueLanguage
dc.contributor.authorZhu, Y-
dc.contributor.authorYeung, CH-
dc.contributor.authorLam, EYM-
dc.date.accessioned2020-11-02T05:46:05Z-
dc.date.available2020-11-02T05:46:05Z-
dc.date.issued2020-
dc.identifier.citationDigital Holography and Three-Dimensional Imaging Meeting in Imaging and Applied Optics Congress, Washington, DC, USA, 22–26 June 2020, paper HTu5B.1-
dc.identifier.isbn9781943580774-
dc.identifier.urihttp://hdl.handle.net/10722/290715-
dc.descriptionSession: Learning-based Approaches in Digital Holography II (HTu5B) - paper HTu5B.1-
dc.description.abstractAn inline digital holography with deep learning is developed to detect microplastics automatically from the raw holograms, without any additional image processing and analysis.-
dc.languageeng-
dc.publisherOptical Society of America.-
dc.relation.ispartofImaging and Applied Optics Congress-
dc.rightsImaging and Applied Optics Congress. Copyright © Optical Society of America.-
dc.titleAutomatic Detection of Microplastics by Deep Learning Enabled Digital Holography-
dc.typeConference_Paper-
dc.identifier.emailYeung, CH: chjyeung@hku.hk-
dc.identifier.emailLam, EYM: elam@eee.hku.hk-
dc.identifier.authorityYeung, CH=rp02422-
dc.identifier.authorityLam, EYM=rp00131-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1364/DH.2020.HTu5B.1-
dc.identifier.hkuros318387-
dc.identifier.spagepaper HTu5B.1-
dc.identifier.epagepaper HTu5B.1-
dc.publisher.placeUnited States-

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