dc.contributor.advisor | Jahan, Sifat E | |
dc.contributor.advisor | Mostakim, Moin | |
dc.contributor.author | Muhtashima, Fawzia | |
dc.contributor.author | Maksurah, Fawzia | |
dc.date.accessioned | 2024-04-24T06:11:11Z | |
dc.date.available | 2024-04-24T06:11:11Z | |
dc.date.copyright | 2023 | |
dc.date.issued | 2023-05 | |
dc.identifier.other | ID 19101204 | |
dc.identifier.uri | http://hdl.handle.net/10361/22664 | |
dc.description | This 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.description | Cataloged from PDF version of thesis. | |
dc.description | Includes 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.statementofresponsibility | Fawzia Muhtashima | |
dc.description.statementofresponsibility | Fawzia Maksurah | |
dc.format.extent | 21 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 | Color prediction | en_US |
dc.subject | Decision tree | en_US |
dc.subject | Linear regression | en_US |
dc.subject | Neural network | en_US |
dc.subject | Feature Engineering | en_US |
dc.subject.lcsh | Machine learning | |
dc.subject.lcsh | Neural networks (Computer science) | |
dc.title | Automated fabric color prediction | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B.Sc. in Computer Science | |