dc.contributor.author | Ishrak, Mohammed Hasin | |
dc.date.accessioned | 2018-11-07T06:22:52Z | |
dc.date.available | 2018-11-07T06:22:52Z | |
dc.date.copyright | 2018 | |
dc.date.issued | 2018 | |
dc.identifier.other | ID 14101180 | |
dc.identifier.uri | http://hdl.handle.net/10361/10819 | |
dc.description | This 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.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 32-38). | |
dc.description.abstract | Cosmic 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 =5 109. We expect to
use more accurate simulation to produce data set to improve the con dence
of the model. | en_US |
dc.description.statementofresponsibility | Mohammed Hasin Ishrak | |
dc.format.extent | 38 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University | en_US |
dc.rights | BRAC 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.subject | Cosmic background radiation | en_US |
dc.subject | Physics simulation | en_US |
dc.subject | Cosmology | en_US |
dc.subject | Cosmic string | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Cosmic data science | en_US |
dc.subject | Early universe | en_US |
dc.subject.lcsh | Neural networks (Computer science) | |
dc.title | Cosmic super string detection using dilated convolutional neural network with focal loss | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, BRAC University | |
dc.description.degree | B. Computer Science and Engineering | |