Fashion Recommendation System

EasyChair Preprint 10013

Abstract

Artificial intelligence is becoming more and 
more helpful in producing individualized product reviews 
on e-commerce websites, person-specific ads, categorizing 
goods, and identifying colors in photographs. One of the 
most important sectors in our world now is fashion. One 
of the main ways that people now show their personalities 
is through their sense of style. They set themselves apart 
from people nearby. In this project, we're creating a 
fashion recommender device that uses artificial 
intelligence to categorize a person's attire and select the 
best clothing for a specific occasion using a 
recommendation algorithm. Unlike traditional structures 
that rely on a customer's past purchases and records, this 
project aims to use a customer-provided image of a 
product as input to produce suggestions because often 
individuals see something they are interested in 
purchasing. interested in and have the propensity to 
search for goods that are comparable to that. According 
to the prototype system, it could assess the user's attire 
from photos, choose the style and color of the attire, and 
then, based on the user's present attire, suggest the most 
appropriate outfit for the event. Users can save images 
of their clothes in the system's closet. To categorize the 
type of apparel in photographs, we investigate machine 
learning and deep learning algorithms.

Keyphrases: CNN, Fashion, Python, Recommendation System, deep learning, e-commerce, image processing

@booklet{EasyChair:10013,
  author    = {Harishankar Yadav and Pradhuman Sharma and Alemnge Nadine and Amit Kumar},
  title     = {Fashion Recommendation System},
  howpublished = {EasyChair Preprint 10013},
  year      = {EasyChair, 2023}}