Analysis of Clothing Image Classification Models: A Comparison Study between Traditional Machine Learning and Deep Learning Models

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dc.contributor.authorXu, Jun
dc.contributor.authorWei, Yumeng
dc.contributor.authorWang, Aichun
dc.contributor.authorZhao, Heng
dc.contributor.authorLefloch, Damien
dc.contributor.organizationTiangong University, Tianjin, China
dc.contributor.organizationShenzhen Technology University, Shenzhen, China
dc.date.accessioned2025-06-03T10:35:02Z
dc.date.available2025-06-03T10:35:02Z
dc.date.issued2022-12-22
dc.description.abstractClothing image in the e-commerce industry plays an important role in providing customers with information. This paper divides clothing images into two groups: pure clothing images and dressed clothing images. Targeting small and medium-sized clothing companies or merchants, it compares traditional machine learning and deep learning models to determine suitable models for each group. For pure clothing images, the HOG+SVM algorithm with the Gaussian kernel function obtains the highest classification accuracy of 91.32% as compared to the Small VGG network. For dressed clothing images, the CNN model obtains a higher accuracy than the HOG+SVM algorithm, with the highest accuracy rate of 69.78% for the Small VGG network. Therefore, for end-users with only ordinary computing processors, it is recommended to apply the traditional machine learning algorithm HOG+SVM to classify pure clothing images. The classification of dressed clothing images is performed using a more efficient and less computationally intensive lightweight model, such as the Small VGG network.en
dc.identifier.citationXu, Jun, et al. "Analysis of Clothing Image Classification Models: A Comparison Study between Traditional Machine Learning and Deep Learning Models" Fibres & Textiles in Eastern Europe, vol. 30, no. 5, Sciendo, 2022, pp. 66-78. https://doi.org/10.2478/ftee-2022-0046
dc.identifier.doi10.2478/ftee-2022-0046
dc.identifier.issn1230-3666
dc.identifier.issn2300-7354
dc.identifier.urihttps://open.icm.edu.pl/handle/123456789/25912
dc.language.isoen
dc.publisherSciendo
dc.relation.ispartofseries30; 5
dc.rightsUznanie autorstwa-Użycie niekomercyjne-Bez utworów zależnych 3.0 Unporteden
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/
dc.sourceFibres & Textiles in Eastern Europe
dc.subjecte-commerceen
dc.subjectclothing image classificationen
dc.subjecttraditional machine learningen
dc.subjectCNNen
dc.subjectHOG+SVMen
dc.subjectsmall VGG networken
dc.titleAnalysis of Clothing Image Classification Models: A Comparison Study between Traditional Machine Learning and Deep Learning Modelsen
dc.typearticle
dc.type.versionpublishedVersion
person.identifier.orcidXu, Jun [0000-0002-0966-399X]
person.identifier.orcidWei, Yumeng [0000-0003-2025-8888]
person.identifier.orcidZhao, Heng [0000-0002-8505-6649]
person.identifier.orcidLefloch, Damien [0000-0002-4812-2790]
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