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
- Nihal Anil, Ms. Nighila Abhish, Jesila Joy , Noora Sajil , P R Vishnuraj, Augmented Neat Algorithm For Enhanced Cognitive Interaction (NEAT-X) , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Mishal Rose Thankachan, Joshua John Sajit, Merwin Maria Antony, Richa Maria Biju, Richa Maria Biju, Bini M Issac, Pixelyse : ViT- VAE for Document Forgery Detection , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Kashinath Remeshkumar, Abhijith R R Abhijith, Dan Philip Bobby, Kevin Varghese Theveril, Hema H H Hema, Zero Shot Low Light Image Enhancement using Vision Language Models and Semantic Diffusion , International Journal on Emerging Research Areas: Vol. 6 No. 1 (2026): IJERA
- Anakin Rajeev, Arya B, Mekha Jose, Archanamol Lalu , Bhadra J , Hand Gesture Recognition Using Deep Learning Techniques-Review , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Selin Sam, Ameen Shouketh, Eby Jo, Jithin Russel, Joyal Anto, Muhammed Nihal K, Animal Detection Using Footprint , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Abid Muhammad, Alan Abdul Gafar, Abin Melvin, Bibin Varghese, A Two-Stage Deep Learning Framework for Skin Lesion Detection and Classification Using ResNet18 and EfficientNet-B4 , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Sebastian Biju, Samuel Michael, Thomas Mathew Jose, Mathew Abraham, Minu Cherian, A Review of Machine Learning Approaches for Canine Skin Disease Detection Using Image Processing Techniques , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Avinash Krishnan, Belda Ben Thomas, Fr Siju John, Bava Kurian Varghese, Ajumon C Thampi, Computer Aided Carbon Footprint Estimation in Educational Institutions , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Shiney Thomas, Elsa George, Alphonsa Francis, Anna Job, Ann Maria James, Wildlife Detection And Recognition Using YOLO V8 , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Abhijith J, Athul Krishna S, Amarthyag P, Angela Rose Baby, Mekha Jose, CATARACT DETECTION USING DIGITAL CAMERA IMAGES , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
You may also start an advanced similarity search for this article.
