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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Smart Fashion Recommendation System using CNN Res-Net 50 |
| Authors Name: | Sneha A , Abijai K T , Vivek Raj K , G. Thiagaranjan , I. Bildass Santhosam |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_191175
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| Published Paper Id: | IJNRD2304339 |
| Published In: | Volume 8 Issue 4, April-2023 |
| DOI: | |
| Abstract: | 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. |
| Keywords: | Res-Net 50, CNN (Convolutional Neural Network), Collaborative Filtering, Privacy, AI, Image Classification. |
| Cite Article: | "Smart Fashion Recommendation System using CNN Res-Net 50", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.d272-d277, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304339.pdf |
| Downloads: | 000118749 |
| 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 |
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Published Paper ID:IJNRD2304339 Registration ID: 191175 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: d272-d277 Country: The Nilgiris, Tamil Nadu, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2304339 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2304339 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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