Neural Network Wardrobe Consultant based on ResNet50
Author(s):
Anmol Singh, Md. Saba Hasmi, Sandeep Kumar
Keywords:
Application of CNN Algorithm, ResNet50, Application of Image Processing, Content-Based Filtering for Recommendation System, CNN Algorithm-Based Feature Extraction, and Outfit Recommendation System, Ecommerce, and Applications of Machine Learning.
Abstract
People began to pay more attention to fashion, which is considered a popular form of aesthetic expression, as their level of living increased. Anything with greater visual appeal will always compel others to gravitate towards it. The evolution of the fashion business may be attributed to human propensity. Nonetheless, the abundance of clothing selections within an online stores has created additional difficulties for clients in selecting the appropriate ensemble. Accordingly, we presented a customised Fashion Based on user input, the recommender system in this study provides recommendations to the user. Instead than relying on the user's prior purchases and history like traditional systems do, this project aims to produce suggestions based on an image of a product submitted by the user. This is because people frequently find products that pique their interest when they see something they like. To analyse the photos from the DeepFashion dataset and provide the final suggestions, we employ CNN powered by a nearest neighbour recommender. Using the newest styles for both clothing and accessoriesand accessories have now evolved into an essential part of daily living. It boosts self-esteem and aids in someone's appealing. People are becoming more conscious of their looks, which is causing them to follow new trends and increase demand for trendy items. With the growing demand for stylish products, a large number of people are entering the fashion and textile sectors. However, there will also be fashion modifications on this trip. There are several types of fashion lifecycles, depending on how long a trend lasts. The typical lifespan of a certain fashion defines its "normal" lifetime. As a result, fads and fashions gain popularity quickly but do not stay forever. These cycles of fashion are called "fads." Fashion that is considered "classic" is designed to last a longer period of time. If a businessperson possesses analytical expertise, it becomes simpler for them to forecast future changes in fashion. Customers will benefit from it in this way as well. The correct fashion guidance will be given to the customer to ensure that their money is invested appropriately, and Appropriate business choices will be made to avoid
Article Details
Unique Paper ID: 163547

Publication Volume & Issue: Volume 10, Issue 11

Page(s): 2321 - 2332
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