Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/589818
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dc.coverage.spatial
dc.date.accessioned2024-09-18T04:14:57Z-
dc.date.available2024-09-18T04:14:57Z-
dc.identifier.urihttp://hdl.handle.net/10603/589818-
dc.description.abstractThe history and usage of Tamil are among the longest of any Indian language. It newlinegoes back to antiquity, has its own tradition, and is steeped in a wealth of ancient literature. newlineAs the new millennium began, more than 66 million people spoke Tamil as their newlinenative tongue. In recent times applications involving image synthesis for the text information newlinehas gained attention to a greater extent. The ability to convert text into imagery newlineusing computer vision techniques involves language model and Generative Adversarial newlineArchitecture (GAN). The current state of intelligent systems research has seen them newlinetaught in universal language but has fallen short of expectations when it comes to applications newlinein regional languages. By eliminating the language barrier, regional languages newlinewill allow for a wider variety of applications to be created and additional fields of study newlineto be investigated. Existing work incorporating auto encoders had limitations in representing newlineoutput features and critical aspects of the synthesised images. In the proposed newlineresearch work a linguistic model is used to generate embedding vectors for the Tamil newlinesentence, and then a GAN is used to synthesise the representation of the image. To improve newlinethe performance of the architecture the design is optimised by considering the input newlinenoise dimensionality and L1 norm for matching features across the real images and newlinesynthesised images. The suggested architecture has several conceivable applications, newlinesuch in the fields of fashion design, photography, Computer Aideed Design (CAD), the newlineeducational sector, and more. Research concepts in native languages can be brought newlinetogether through the use of the proposed language and image synthesis deep learning newlinearchitecture. The evaluation of proposed model has achieved performance when compared newlinewith state-of-art models for image synthesis for Tamil language newline newline
dc.format.extenti-x,108
dc.languageEnglish
dc.relation
dc.rightsuniversity
dc.titleText to Image Synthesis Model for Tamil Language based on Deep Learning Approach
dc.title.alternative
dc.creator.researcherDiviya, M
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Interdisciplinary Applications
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideKarmel, A
dc.publisher.placeVellore
dc.publisher.universityVellore Institute of Technology, Vellore
dc.publisher.institutionSchool of Computing Science and Engineering VIT-Chennai
dc.date.registered2019
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:School of Computing Science and Engineering VIT-Chennai

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01_title.pdfAttached File49.18 kBAdobe PDFView/Open
02_prelim pages.pdf120.91 kBAdobe PDFView/Open
03_content.pdf43.13 kBAdobe PDFView/Open
04_abstract.pdf59.13 kBAdobe PDFView/Open
05_chapter 1.pdf3.66 MBAdobe PDFView/Open
06_chapter 2.pdf86.8 kBAdobe PDFView/Open
07_chapter 3.pdf9.27 MBAdobe PDFView/Open
08_chapter 4.pdf2.18 MBAdobe PDFView/Open
09_chapter 5.pdf4.6 MBAdobe PDFView/Open
10_chapter 6.pdf42.94 kBAdobe PDFView/Open
11_annexure.pdf72.64 kBAdobe PDFView/Open
80_recommendation.pdf73.91 kBAdobe PDFView/Open


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