Personalized recognition system in online shopping by using deep learning

EAI Endorsed Transactions on Internet of Things Pub Date : 2024-01-10 DOI:10.4108/eetiot.4810

Manjula Devarakonda Venkata, Prashanth Donda, N. B. Madhavi, Pavitar Parkash Singh, A. Azhagu, Jaisudhan Pazhani, Shaik Rehana Banu

引用次数: 0

Abstract

This study presents an effective monitoring system to watch the Buying Experience across multiple shop interactions based on the refinement of the information derived from physiological data and facial expressions. The system's efficacy in recognizing consumers' emotions and avoiding bias based on age, race, and evaluation gender in a pilot study. The system's data has been compared to the outcomes of conventional video analysis. The study's conclusions indicate that the suggested approach can aid in the analysis of consumer experience in a store setting.

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利用深度学习的在线购物个性化识别系统

本研究基于从生理数据和面部表情中提取的信息的改进，提出了一种有效的监测系统，用于在多次商店互动中观察购买体验。在一项试点研究中，该系统有效识别了消费者的情绪，避免了基于年龄、种族和评价性别的偏见。该系统的数据与传统的视频分析结果进行了比较。研究结论表明，建议的方法有助于分析消费者在商店环境中的体验。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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EAI Endorsed Transactions on Internet of Things

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