JEWELLERY SHOPPING WITH FACIAL RECOGNITION
Abstract
New potential for personalisation are presented by the developing nexus between artificial intelligence and e-commerce. This study presents a cutting-edge jewelry recommendation system that revolutionizes online buying by leveraging computer vision and machine learning. The technology uses Convolutional Neural Networks (CNNs) to analyse user-uploaded facial photos and produce customised jewellery recommendations based on skin tone, face shape, and specific facial features. The methodology creates a novel way to personalised product discovery by combining sophisticated image processing techniques with a hybrid recommendation system. The platform connects digital interfaces with personal aesthetic preferences by using intelligent matching and multi-stage facial analysis. The system's ability to improve user engagement is demonstrated via experimental validation, providing a revolutionary
Keywords:
cutting-edge, artificial intelligence, computer visionPublished
Issue
Section
License
Copyright (c) 2025 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Amal P Varghese , Juby Mathew, Advancements in Vehicular Communication Systems: Integrating IoT, Edge Cloud Computing, Microgrid Energy Management, Blockchain, AI, and Simulation Tools , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- B Bidhun, Deepak Dayanandan, Joel Joy, Vargheese Francis, Vani V Prakash, A Comprehensive Review of Lightweight and Attention-Driven Deep Learning Models for Automated Cataract Detection , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Parvathy V A, Irfana Parveen C A, Alisha K A, Reshma P R, Manu Krishna C P, Detection of Diabetic Retinopathy and Glaucoma using Deep Learning , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Merin Wilson, Muhammed Sajid N, Nandana L P, Nanda Santhosh, Rahul M, Mekha Jose, A Review on Deep Learning and IoT-Based Road Surface Damage Detection , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Honey Joseph, Aaron Samuel Mathew, Adhil P, Alan Siby, Alwyn Joseph, Potato Leaf Disease Detection Using VIT , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Betzy Babu Thoppil, Anugrah Premachandran, Annapoorna M, Ashwin Mathew Zachariah, Bala Susan Jacob, Advanced Sensor-Based Landslide and Earthquake Detection and Alert System Utilizing Machine Learning and Computer Vision Technologies , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Athul Das, Dan Kuruvilla, Amrutha P Chandran, Blesson V Monichan, Elias Janson K, TRIMBOT: AUTONOMOUS GRASS CUTTING ROBOT USING GPS NAVIGATION , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Anitta K Mathew, Hanna Sarah Sabu, Annu Alphonse Jojo, Helan Poulose, Lia Maria Rajan, A Review of AI-Powered Tools to Help People With Visual Impairments , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Sumi Joseph, Diana George, Ruthi Namburi, Dhanya Prathap, Artificial Intelligence in Opthamology:A study on different AIML approaches for Glaucoma prediction , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Albin Thomas Lalu, Resmara S, Alen A Thankachen, Sneha Priya Sebastian, Dany Jennez , Lirin Blesson, Kesia Sunny, Fault Detection of Transmission Lines Using Unmanned Aerial Vehicle (UAV) , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
You may also start an advanced similarity search for this article.
