Implementation of online and offline product selection system using FCNN deep learning: Product analysis

Mohammad, Mohammad Noor; Kumari, Ch. Usha; Murthy, A. Sampath Dakshina; Jagan, B. Omkar Lakshmi; Saikumar, K.

doi:10.1016/j.matpr.2020.10.072

Cited by 40 publications

(17 citation statements)

References 18 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%

“…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%

See 1 more Smart Citation

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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Section: Methods Citationsmentioning

confidence: 99%

Section: Databases Citationsmentioning

confidence: 99%

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

Goti,

Querejeta-Lomas,

Almeida

et al. 2023

Mathematics

View full text Add to dashboard Cite

show abstract

“…Additionally, a random forest model utilizing product titles achieved superior accuracy, compared to SVM and CNN, for the classification of e-commerce products [187]. On the other hand, image recognition techniques have been extensively explored in the field of fashion and clothing product classification, employing various machine learning and deep learning models such as CNN, CNN-RNN, transfer learning, SVM-CNN, and LSTM to accurately categorize products [188][189][190][191][192][193][194][195][196]. These studies emphasize the vital role of advanced machine learning and deep learning techniques in enhancing product classification, image recognition, and categorization in the e-commerce industry.…”

Section: Product Classification and Image Recognitionmentioning

confidence: 99%

A Brief Survey of Machine Learning and Deep Learning Techniques for E-Commerce Research

Zhang,

Guo,

Chen

et al. 2023

JTAER

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The rapid growth of e-commerce has significantly increased the demand for advanced techniques to address specific tasks in the e-commerce field. In this paper, we present a brief survey of machine learning and deep learning techniques in the context of e-commerce, focusing on the years 2018–2023 in a Google Scholar search, with the aim of identifying state-of-the-art approaches, main topics, and potential challenges in the field. We first introduce the applied machine learning and deep learning techniques, spanning from support vector machines, decision trees, and random forests to conventional neural networks, recurrent neural networks, generative adversarial networks, and beyond. Next, we summarize the main topics, including sentiment analysis, recommendation systems, fake review detection, fraud detection, customer churn prediction, customer purchase behavior prediction, prediction of sales, product classification, and image recognition. Finally, we discuss the main challenges and trends, which are related to imbalanced data, over-fitting and generalization, multi-modal learning, interpretability, personalization, chatbots, and virtual assistance. This survey offers a concise overview of the current state and future directions regarding the use of machine learning and deep learning techniques in the context of e-commerce. Further research and development will be necessary to address the evolving challenges and opportunities presented by the dynamic e-commerce landscape.

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“…Static WPT charges the battery while the vehicle is parked, while dynamic WPT charges the battery when the vehicle is moving on a WPT-configured road. Sustainable mobility and the elimination of certain barriers to vehicle electrification could be within reach with the assistance of the WPT for electric automobiles [20]. Due to this outcome, corded chargers would be superfluous.…”

Section: Introductionmentioning

confidence: 99%

V2G Nonlinear Connection in EV’s for Wireless and Sustainable Mobility with Support of Machine Learning

Sudeepthi Govathoti

2024

cana

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In order to achieve reliable, rapid, and affordable charging solutions, this study examines the several approaches and strategies used in electric vehicle wireless charging systems. Wireless charging offers an eco-friendly and user-friendly alternative to standard cable systems by doing away with the need for physical connections. In the first section of the review, presented below are the numerous modes of wireless power transfer, with an emphasis on the inductive & capacitive methods. Next, the essay delves into the several kinds of electric vehicle wireless charging systems, including mobile and static alternatives, and how they are categorised. Noteworthy to this research is its examination of dynamic charging systems' standard model and design characteristics, which enable wireless charging in moving vehicles. It also shows how important control system features are for effective power transmission and communication between charging receiver and transmitter parts. In addition to reviewing various battery models and comparing various types of batteries, the article acknowledges the crucial function that batteries play in electric vehicles and highlights how they affect the parameters of the charging system. Finally, the paper delves into a discussion of its findings and makes suggestions for further research in this area.

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Implementation of online and offline product selection system using FCNN deep learning: Product analysis

Cited by 40 publications

References 18 publications

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

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

A Brief Survey of Machine Learning and Deep Learning Techniques for E-Commerce Research

V2G Nonlinear Connection in EV’s for Wireless and Sustainable Mobility with Support of Machine Learning

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