Skip to content

Content Based Image Retrieval, otherwise known as ‘CBIR’ is a method used to extract visually similar images from a large database, based on the features of a given query image. This project explores and presents a modified approach to CBIR by using artificial neural networks, as opposed to classical computer vision techniques. The method presen…

Notifications You must be signed in to change notification settings

pascalemp/CBIR-siamese-cnn

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

34 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Useful Information

This project was created at University as part of my final year project in order to learn more about the use of Convolutional Neural Networks and their efficacy within the branch of computer vision known as Content Based Image Retrieval.

You can access the PDF write-up here.

The datasets used within this project were the Omniglot dataset and a modifed version of the Stanford Dogs dataset.

The network architecture is based on that of Gregory Koch et al. with the original paper is listed here.

About

Content Based Image Retrieval, otherwise known as ‘CBIR’ is a method used to extract visually similar images from a large database, based on the features of a given query image. This project explores and presents a modified approach to CBIR by using artificial neural networks, as opposed to classical computer vision techniques. The method presen…

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages