Auto-Encoders for Content-based Image Retrieval with its Implementation Using Handwritten Dataset
Vaibhav Rupapara, Manideep Narra, Naresh Kumar Gonda, Kaushika Thipparthy, Swapnil Gandhi
Abstract
Image retrieval technology is a very fast-growing digital technology for researchers in the field of computer science from a very long period. It is a system for retrieving digital images from a large database. The well-known organizations that are using this system are Google and Pinterest. In this conference paper, a content-based image retrieval system that uses an innovative type of neural network known as autoencoder is discussed and developed a basic system to understand it. The methodology that has been used is an unsupervised method which is a machine learning algorithm in which the system retrieves images without searching about its name, labels, and tags. This system retrieves images just by its visual information. This approach of image retrieval is known as Content-Based Image Retrieval (CBIR).