Classification of different magnetic structures from image data using deep neural networks

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.

书目详细资料
Main Authors:	Ibn Hasib, Fahad, Swarna, Nakiba Farhana
其他作者:	Alam, Dr. Md. Ashraful
格式:	Thesis
语言:	English
出版:	Brac University 2023
主题:	Deep Neural Network Magnetic structure Image classification Machine learning Res-Net Neural networks (Computer science)
在线阅读:	http://hdl.handle.net/10361/18737

id	10361-18737
record_format	dspace
spelling	10361-187372023-07-11T21:05:18Z Classification of different magnetic structures from image data using deep neural networks Ibn Hasib, Fahad Swarna, Nakiba Farhana Alam, Dr. Md. Ashraful Department of Computer Science and Engineering, Brac University Deep Neural Network Magnetic structure Image classification Machine learning Res-Net Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 37-39). We apply machine learning, specially deep neural network approaches, to train a new model that can perform an effective classification of ferromagnetic, anti ferromagnetic, skyrmion, anti-skyrmion and spin spiral configurations via supervised learning and also observe how the pre trained models like VGG16, VGG19, ResNet, Inception behave while solving this problem, draw a pattern from it and suggest path for further improving the model. The problem relies in categorization of Mag netic Configurations amongst many from input samples of simulation data in order to retrieve classified outcome from several different magnetic configurations. The data for the input sample derives from simulations of physical properties of various magnetic configurations. First CNN is used to classify between the images. Image classifications are mostly carried out using neural networks where data is placed in a graphical structure. In addition, the SVM method is applied twice, once with PCA and once without PCA. The proposed model in this research paper can success fully classify amongst magnetic configurations in real time with data obtained from spin-polarized scanning tunneling and Lorentz transmission electron microscopy. In our approach, we used a single deep neural network architecture is classify all five types of magnetic structures. All in all, this is a holistic approach for solving the classification problem of magnetic configuration and taking a step into optimizing the model. Fahad Ibn Hasib Nakiba Farhana Swarna B. Computer Science 2023-07-11T09:17:59Z 2023-07-11T09:17:59Z 2021 2021-09 Thesis ID: 21141002 ID: 21341054 http://hdl.handle.net/10361/18737 en 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. 39 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Deep Neural Network Magnetic structure Image classification Machine learning Res-Net Neural networks (Computer science)
spellingShingle	Deep Neural Network Magnetic structure Image classification Machine learning Res-Net Neural networks (Computer science) Ibn Hasib, Fahad Swarna, Nakiba Farhana Classification of different magnetic structures from image data using deep neural networks
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.
author2	Alam, Dr. Md. Ashraful
author_facet	Alam, Dr. Md. Ashraful Ibn Hasib, Fahad Swarna, Nakiba Farhana
format	Thesis
author	Ibn Hasib, Fahad Swarna, Nakiba Farhana
author_sort	Ibn Hasib, Fahad
title	Classification of different magnetic structures from image data using deep neural networks
title_short	Classification of different magnetic structures from image data using deep neural networks
title_full	Classification of different magnetic structures from image data using deep neural networks
title_fullStr	Classification of different magnetic structures from image data using deep neural networks
title_full_unstemmed	Classification of different magnetic structures from image data using deep neural networks
title_sort	classification of different magnetic structures from image data using deep neural networks
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/18737
work_keys_str_mv	AT ibnhasibfahad classificationofdifferentmagneticstructuresfromimagedatausingdeepneuralnetworks AT swarnanakibafarhana classificationofdifferentmagneticstructuresfromimagedatausingdeepneuralnetworks
_version_	1814308559318417408

Classification of different magnetic structures from image data using deep neural networks

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