Editorial
Personalized recognition system in online shopping by using deep learning
@ARTICLE{10.4108/eetiot.4810, author={Manjula Devarakonda Venkata and Prashanth Donda and N. Bindu Madhavi and Pavitar Parkash Singh and A. Azhagu Jaisudhan Pazhani and Shaik Rehana Banu}, title={Personalized recognition system in online shopping by using deep learning}, journal={EAI Endorsed Transactions on Internet of Things}, volume={10}, number={1}, publisher={EAI}, journal_a={IOT}, year={2024}, month={1}, keywords={Customer emotions, conventional analysis, customer experience, Deep learning}, doi={10.4108/eetiot.4810} }- Manjula Devarakonda Venkata
Prashanth Donda
N. Bindu Madhavi
Pavitar Parkash Singh
A. Azhagu Jaisudhan Pazhani
Shaik Rehana Banu
Year: 2024
Personalized recognition system in online shopping by using deep learning
IOT
EAI
DOI: 10.4108/eetiot.4810
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.
Copyright © 2024 M. D. Venkata et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
