Smart Fashion Recommendation System using CNN Res-Net 50

Registration ID: IJNRD_191175

Published ID: IJNRD2304339

DOI: Click Here to Get

Sneha A , Abijai K T , Vivek Raj K , G. Thiagaranjan , I. Bildass Santhosam

Res-Net 50, CNN (Convolutional Neural Network), Collaborative Filtering, Privacy, AI, Image Classification.

A fashion recommender system is a methodology that is based on Artificial intelligence usually associated with machine learning that suggests clothing items to users based on their preferences and previous shopping behavior. A recommender is used to predict the preference and ratings of the user for an item based on the profile and the search history of the user. It is a powerful technique in terms of business because Google, Facebook and e-commerce websites use recommender systems to expand their business. There are mainly two types of recommender system that exists. First, Content-based filtering is based on the profile of the user and the featurization of items, and Second, Collaborative filtering involves the user's past behavior and the user's previous utility with the different items. Our proposed system aims to develop a fashion recommender system using a pre-trained Res-Net 50 CNN model. We strive to build a fashion recommender system that is programmed to recommend the predicted clothing images or items from a large set of collected images. Our proposed system is implemented using collaborative filtering techniques and also considers the privacy and security concerns related to collecting and storing user data. Our proposed system is expected to provide accurate and diverse recommendations to users, thereby assisting them in their clothing choices.

Published Paper   E-Certificate

Sneha A, Abijai K T, Vivek Raj K, G. Thiagaranjan, & I. Bildass Santhosam (April-2023). Smart Fashion Recommendation System using CNN Res-Net 50. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), d272-d277. https://ijnrd.org/papers/IJNRD2304339.pdf

Volume 8 Issue 4, April-2023

Pages : d272-d277

Paper Reg. ID: IJNRD_191175

Published Paper Id: IJNRD2304339

Downloads: 000121987

Research Area: Information Technology 

Country: The Nilgiris, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304339.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304339

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave | IJNRD.ORG | IJNRD.COM | IJPUB.ORG

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 10 | October 2025

IJNRD is a Scholarly Open Access, Peer-reviewed, and Refereed Journal with a High Impact Factor of 8.76 (calculated by Google Scholar & Semantic Scholar | AI-Powered Research Tool). It is a Multidisciplinary, Monthly, Low-Cost Journal that follows UGC CARE 2025 Peer-Reviewed Journal Policy norms, Scopus journal standards, and Transparent Peer Review practices to ensure quality and credibility. IJNRD provides indexing in all major databases & metadata repositories, a citation generator, and Digital Object Identifier (DOI) for every published article with full open-access visibility.

The INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to advance applied, theoretical, and experimental research across diverse fields. Its goal is to promote global scientific information exchange among researchers, developers, engineers, academicians, and practitioners. IJNRD serves as a platform where educators and professionals can share research evidence, models of best practice, and innovative ideas, contributing to academic growth and industry relevance.

Indexing Coverage includes Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar (AI-Powered Research Tool), Microsoft Academic, Academia.edu, arXiv.org, ResearchGate, CiteSeerX, ResearcherID (Thomson Reuters), Mendeley, DocStoc, ISSUU, Scribd, and many more recognized academic repositories.

How to submit the paper?

By Our website

Click Here to Submit Paper Online

By Mail

Send your paper to editor@ijnrd.org

Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: IJNRD is an International Peer-reviewed, Refereed, and Open Access Journal with Transparent Peer Review as per the new UGC CARE 2025 guidelines, offering low-cost multidisciplinary publication with Crossref DOI and global indexing.

Subject Category: Research Area

Call for Paper: More Details