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dc.contributor.authorIshrak, Mohammed Hasin
dc.date.accessioned2018-11-07T06:22:52Z
dc.date.available2018-11-07T06:22:52Z
dc.date.copyright2018
dc.date.issued2018
dc.identifier.otherID 14101180
dc.identifier.urihttp://hdl.handle.net/10361/10819
dc.descriptionThis thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 32-38).
dc.description.abstractCosmic string are objects of great importance and investigation for cosmic string has been done from last 20 years. There are a lot of models to detect cosmic string.But a very few are to detect the location of cosmic string.We propose a framework to detect the location of cosmic string. We used di- lated convolutional net with focal loss instead of cross-entropy to improved the performance of the framework on weak samples. The neural network we trained is able to detect and locate cosmic string on noiseless CMB temper- ature map down to a string tension of less then G =5 10􀀀9. We expect to use more accurate simulation to produce data set to improve the con dence of the model.en_US
dc.description.statementofresponsibilityMohammed Hasin Ishrak
dc.format.extent38 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectCosmic background radiationen_US
dc.subjectPhysics simulationen_US
dc.subjectCosmologyen_US
dc.subjectCosmic stringen_US
dc.subjectMachine learningen_US
dc.subjectCosmic data scienceen_US
dc.subjectEarly universeen_US
dc.subject.lcshNeural networks (Computer science)
dc.titleCosmic super string detection using dilated convolutional neural network with focal lossen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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