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dc.contributor.advisorJahan, Sifat E
dc.contributor.advisorMostakim, Moin
dc.contributor.authorMuhtashima, Fawzia
dc.contributor.authorMaksurah, Fawzia
dc.date.accessioned2024-04-24T06:11:11Z
dc.date.available2024-04-24T06:11:11Z
dc.date.copyright2023
dc.date.issued2023-05
dc.identifier.otherID 19101204
dc.identifier.urihttp://hdl.handle.net/10361/22664
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 20-21).
dc.description.abstract"This paper focuses on addressing some challenges faced by colorists and explores various approaches to predict fabric color changes after dyeing processes. It empha- sizes the importance of color prediction in the textile industry and proposes suitable models that can effectively carry out color prediction tasks based on given recipes. By implementing such predictive models, the textile industry can improve efficiency, reduce labor-intensive practices, and enhance the overall quality control process. The methods used in this study are supervised machine learning techniques, in- cluding multiple linear regression, decision tree, random forest, and neural network. Among these models, the most appropriate one is selected and further optimized using feature engineering techniques to improve accuracy"en_US
dc.description.statementofresponsibilityFawzia Muhtashima
dc.description.statementofresponsibilityFawzia Maksurah
dc.format.extent21 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.subjectColor predictionen_US
dc.subjectDecision treeen_US
dc.subjectLinear regressionen_US
dc.subjectNeural networken_US
dc.subjectFeature Engineeringen_US
dc.subject.lcshMachine learning
dc.subject.lcshNeural networks (Computer science)
dc.titleAutomated fabric color predictionen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB.Sc. in Computer Science


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