Deep Domain Adaption for Convolutional Neural Network (CNN) based Iris Segmentation: Solutions and Pitfalls

Jalilian, Ehsaneddin; Uhl, Andreas

Deep Domain Adaption for Convolutional Neural Network (CNN) based Iris Segmentation: Solutions and Pitfalls

dc.contributor.author	Jalilian, Ehsaneddin
dc.contributor.author	Uhl, Andreas
dc.contributor.editor	Brömme, Arslan
dc.contributor.editor	Busch, Christoph
dc.contributor.editor	Dantcheva, Antitza
dc.contributor.editor	Rathgeb, Christian
dc.contributor.editor	Uhl, Andreas
dc.date.accessioned	2020-09-15T13:01:31Z
dc.date.available	2020-09-15T13:01:31Z
dc.date.issued	2019
dc.description.abstract	Addressing the lack of massive amounts of labeled training data, deep domain adaptation has been applied successfully in many applications of machine learning. We investigate the application of deep domain adaptation for CNN based iris segmentation, exploring available solutions and their corresponding strengths and pitfalls, with several major contributions. First, we provide a comprehensive survey of current deep domain adaptation methods according to the properties of data that cause the domains divergence. Second, after selecting credible methods, we evaluate their expedience in terms of iris segmentation performance. Third, we analyze and compare the performance against the state-of-the-art methods under these categories. Forth, potential shortfalls of current methods and several future directions are pointed out and discussed.	en
dc.identifier.isbn	978-3-88579-690-9
dc.identifier.pissn	1617-5468
dc.identifier.uri	https://dl.gi.de/handle/20.500.12116/34239
dc.language.iso	en
dc.publisher	Gesellschaft für Informatik e.V.
dc.relation.ispartof	BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseries	Lecture Notes in Informatics (LNI) - Proceedings, Volume P-297
dc.subject	Deep domain adaptation
dc.subject	iris segmentation
dc.subject	convolutional neural networks.
dc.title	Deep Domain Adaption for Convolutional Neural Network (CNN) based Iris Segmentation: Solutions and Pitfalls	en
dc.type	Text/Conference Paper
gi.citation.endPage	70
gi.citation.publisherPlace	Bonn
gi.citation.startPage	59
gi.conference.date	18.-20. September 2019
gi.conference.location	Darmstadt, Germany
gi.conference.sessiontitle	Regular Research Papers

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