Salvato in:
| Autori principali: | , , , , , , , |
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| Natura: | Recurso digital |
| Lingua: | |
| Pubblicazione: |
Zenodo
2025
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| Accesso online: | https://doi.org/10.5281/zenodo.15543236 |
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Sommario:
- <p>New potential for personalisation are presented by the developing nexus between artificial intelligence and e-commerce. This study presents a cutting-edge jewellery recommendation system that revolutionises 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 solution in personalised e-commerce technology. </p>