Abstract— The goal of this project is to provide product recommendations using image search. The recommendations will be provided on the basis of image similarity using the ResNet50 model. The ResNet model is a technique that uses deep learning to recommend items based on their visual similarity. The system allows users to upload an image of a product and then retrieves similar products from a database based on the visual features extracted from the image using the ResNet50 model. The nearest neighbor algorithm is used to find the most similar products to the uploaded image based on the Euclidean distance between the feature vectors. The top five most similar products are returned and displayed to the user
In recent years, the expansion of the Internet has brought an explosion of visual information, inclu...
This master´s thesis deals with the reseach of technologies using deep learning method, being able t...
Recommendation systems typically use historical interactions between users and items topredict what ...
Visual similarity recommendations have an immense role in E-commerce portals. Fetching the appropria...
In this paper, we compare the results of ResNet image classification with the results of Google Imag...
ABSTRACT- The project concentrated on developing and providing the customers or users a more simplif...
The online merchants and users supply rich data everyday on e-commerce websites, this only gets bigg...
In fashion-based recommendation settings, incorporating the item image features is considered a cruc...
Recently, recommendation system (RS) has gained significant attention in several industries and busi...
Online shopping has developed in parallel with the Internet, and Recommendation Systems have played ...
PriceRunner is an online shopping comparison company. To maintain up-todate prices, PriceRunner has ...
Abstract — The goal of this paper is to develop an image search and similarity founding system using...
Engines for browsing image databases are usually based on predefined fea- tures for selecting the im...
As a scene graph compactly summarizes the high-level content of an image in a structured and symboli...
This paper presents a method for improving object search accuracy using a deep learning model. A maj...
In recent years, the expansion of the Internet has brought an explosion of visual information, inclu...
This master´s thesis deals with the reseach of technologies using deep learning method, being able t...
Recommendation systems typically use historical interactions between users and items topredict what ...
Visual similarity recommendations have an immense role in E-commerce portals. Fetching the appropria...
In this paper, we compare the results of ResNet image classification with the results of Google Imag...
ABSTRACT- The project concentrated on developing and providing the customers or users a more simplif...
The online merchants and users supply rich data everyday on e-commerce websites, this only gets bigg...
In fashion-based recommendation settings, incorporating the item image features is considered a cruc...
Recently, recommendation system (RS) has gained significant attention in several industries and busi...
Online shopping has developed in parallel with the Internet, and Recommendation Systems have played ...
PriceRunner is an online shopping comparison company. To maintain up-todate prices, PriceRunner has ...
Abstract — The goal of this paper is to develop an image search and similarity founding system using...
Engines for browsing image databases are usually based on predefined fea- tures for selecting the im...
As a scene graph compactly summarizes the high-level content of an image in a structured and symboli...
This paper presents a method for improving object search accuracy using a deep learning model. A maj...
In recent years, the expansion of the Internet has brought an explosion of visual information, inclu...
This master´s thesis deals with the reseach of technologies using deep learning method, being able t...
Recommendation systems typically use historical interactions between users and items topredict what ...