Ishrak, Mohammed Hasin2018-11-072018-11-0720182018ID 14101180http://hdl.handle.net/10361/10819Cataloged from PDF version of thesis.Includes bibliographical references (pages 32-38).This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.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 10􀀀9. We expect to use more accurate simulation to produce data set to improve the con dence of the model.38 pagesenBRAC 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.Cosmic background radiationPhysics simulationCosmologyCosmic stringMachine learningCosmic data scienceEarly universeNeural networks (Computer science)Thesis