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Semantic segmentation of RGBD videos with recurrent fully convolutional neural networks

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dc.contributor.advisorYemez, Yücel
dc.contributor.advisorid0000-0002-7515-3138
dc.contributor.authorYurdakul, Ekrem Emre
dc.contributor.instituteKoç University Graduate School of Sciences and Engineering
dc.contributor.programComputer Science and Engineering
dc.contributor.yokid107907
dc.date.accessioned2024-11-09T22:07:42Z
dc.date.issued2017
dc.descriptionxi, 43 leaves : illustrations ; 30 cm.
dc.identifier.urihttps://hdl.handle.net/20.500.14288/4921
dc.languageEnglish
dc.publisherKoç University
dc.relation.collectionKU Theses and Dissertations
dc.rightsrestrictedAccess
dc.rights.copyrightsnote© All Rights Reserved. Accessible to Koç University Affiliated Users Only!
dc.subjectNeural networks (Computer science)
dc.subjectImage segmentation
dc.subjectImage processing
dc.thesis.degreeMaster's Degree
dc.thesis.grantorİstanbul
dc.titleSemantic segmentation of RGBD videos with recurrent fully convolutional neural networks
dc.typeThesis
dspace.entity.typePublication
relation.isAdvisorOfThesis23c08ce5-6539-43b2-a2fa-ce7e80c2b52d
relation.isAdvisorOfThesis.latestForDiscovery23c08ce5-6539-43b2-a2fa-ce7e80c2b52d

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