Image-to-Image Attire Transfer for Virtual Trial Room

Sanzam, Syed; Das, Sourav; Sifat-Ul-Alam,; Jubair, Mohammad Imrul; Ahmed, Md. Faisal

doi:10.1109/iccit51783.2020.9392671

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…FastkNN [152] FCNN [56] FNN [32] Fuzzylogic [106,113] GAN [71,75,99,129,134,141,155,251] GA-RF [65] GaussianMixtureModels [109,118] gradientboostingdecisiontree [42] GraphCNN [40,122] GraphDCNN [89] GRU [230] GSN [87] H-CNN [39,157] HOG [153] HypergraphNN [80] Imageprocessing [119,120,130,132,135,136,147] k-center [117] k-means [114,203,232,244] k-medoids [115] Kneser-Ney [34] kNN [54,137,222,235,237,250] LAC [107,116] Lassoregression …”

Section: Methods Citationsmentioning

confidence: 99%

“…The fit of virtual clothing is frequently evaluated using neural networks [144], including CNN [140] and GAN variations [141]. The employment of alternative algorithms, such as the naive Bayes (NB) algorithm for classification [149], the Viola-Jones (VJ) algorithm for body tracking [148], or the fuzzy neural network (FNN) [32], has also been the subject of some research.…”

Section: Customer Satisfactionmentioning

confidence: 99%

“…Summary of purposes with references. Sentimentanalysis [42,44,[169][170][171][172][173][174][175][176][177][178][179][180] Virtualfitting [32,[129][130][131][132][133][134][135][136][138][139][140][141][142][143][144][145][146][149][150][151][152] Table 7. Summary of databases with references.…”

Section: R-cnn [59]mentioning

confidence: 99%

“…DeepFashion3D [135] DeepFashion-C [57] DressCode [129] FashionAI2018 [72] FashionDNA [88] Fashionista [108] FashionLandmarkdetection [57] FashionMNIST [39,74,87] Fashion-MNIST [58,62,65,68] FashionVC [166] Feidegger [123] FindFashion [40] GoogleAnalytics [212] ImageNet [47,56,63] Image-Net [157] iPER [141] Kaggle [60,125,173] LookBook [75] MovingFashion [51] MPV [134,140] POG [159] Table 7. Cont.…”

Section: Databases Citationsmentioning

confidence: 99%

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Artificial Intelligence in Business-to-Customer Fashion Retail: A Literature Review

Goti,

Querejeta-Lomas,

Almeida

et al. 2023

Mathematics

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Many industries, including healthcare, banking, the auto industry, education, and retail, have already undergone significant changes because of artificial intelligence (AI). Business-to-Customer (B2C) e-commerce has considerably increased the use of AI in recent years. The purpose of this research is to examine the significance and impact of AI in the realm of fashion e-commerce. To that end, a systematic review of the literature is carried out, in which data from the Web Of Science and Scopus databases were used to analyze 219 publications on the subject. The articles were first categorized using AI techniques. In the realm of fashion e-commerce, they were divided into two categories. These categorizations allowed for the identification of research gaps in the use of AI. These gaps offer potential and possibilities for further research.

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