Investigating the Efficacy of Deep Learning Networks for 3D Imaging and Processing

Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16721

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DC Field	Value	Language
dc.contributor.author	Muniraj, Inbarasan	-
dc.date.accessioned	2024-12-12T09:29:51Z	-
dc.date.available	2024-12-12T09:29:51Z	-
dc.date.issued	2024	-
dc.identifier.isbn	9781957171371	-
dc.identifier.uri	https://opg.optica.org/abstract.cfm?URI=3D-2024-DW1H.4	-
dc.identifier.uri	https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16721	-
dc.description.abstract	Artificial intelligence techniques, such as machine learning (ML) and deep learning (DL), are now widely used in various vision-based applications. Here, we summarize some of the most recent advances in Computational Integral Imaging using DL networks. © 2024 The Author(s).	en_US
dc.language.iso	en	en_US
dc.publisher	Optica Imaging Congress 2024 (3D, AOMS, COSI, ISA, pcAOP)	en_US
dc.publisher	Optical Society of America	en_US
dc.subject	Federated Learning	en_US
dc.subject	3-D Processing	en_US
dc.subject	3D Imaging	en_US
dc.subject	Artificial Intelligence Techniques	en_US
dc.subject	Integral Imaging	en_US
dc.title	Investigating the Efficacy of Deep Learning Networks for 3D Imaging and Processing	en_US
dc.type	Article	en_US
Appears in Collections:	Conference Papers

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