Apparel attributes classification using deep learning

dc.accession.numberT00843
dc.classification.ddc006.31 DES
dc.contributor.advisorJat, P.M
dc.contributor.authorDesai, Harsh Sanjaykumar
dc.date.accessioned2020-09-22T14:07:25Z
dc.date.accessioned2025-06-28T10:27:50Z
dc.date.available2023-02-16T14:07:25Z
dc.date.issued2020
dc.degreeM. Tech
dc.description.abstractApparel attributes classification finds a practical applications in E-Commerce. The project is for www.Blibli.com website which is an E-commerce Platform in Indonesia and a partner of Coviam Technologies. This report describes an approach to classify attributes such as material, neck/collar, sleeves type etc. specific to various apparels using Natural Language Processing and Deep Learning techniques. The classified products based on attributes will be used as filters on search results page to enhance and improve search mechanism of website. We have classified 95% apparel products based on material attribute and achieved 87% test accuracy on neck/collar attribute classification. The report is divided into four main parts which covers: Introduction, DataSet Preparation, Methodology and the Experimentation. Lastly, other similar work performed during internship along with the future work is discussed.
dc.identifier.citationDesai, Harsh Sanjaykumar (2020). Apparel attributes classification using deep learning. Dhirubhai Ambani Institute of Information and Communication Technology. vi, 15 p. (Acc.No: T00843)
dc.identifier.urihttp://drsr.daiict.ac.in/handle/123456789/921
dc.student.id201811011
dc.subjectData science
dc.subjectNatural language processing
dc.subjectDeep learning
dc.subjectRule-based approaches
dc.titleApparel attributes classification using deep learning
dc.typeDissertation

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