Recommender System for Apparel Products Based on Image Recognition Using Convolutional Neural Networks
In e-commerce and fashion, personalized recommendations are used to enhance user experience and engagement. In this study, an apparel recognition and recommender system (ARRS) using convolutional neural networks (CNNs) was employed to analyze apparel images, extract features, and provide accurate re...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/89/1/38 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In e-commerce and fashion, personalized recommendations are used to enhance user experience and engagement. In this study, an apparel recognition and recommender system (ARRS) using convolutional neural networks (CNNs) was employed to analyze apparel images, extract features, and provide accurate recognition and recommendations. By learning patterns and features of clothes, the system enables robust recognition and personalized suggestions. The effectiveness of ARRS in recognizing apparel and generating relevant recommendations was validated. The system enhances user satisfaction and engagement on fashion e-commerce platforms. |
|---|---|
| ISSN: | 2673-4591 |