DeepSeek: Content Based Image Search & Retrieval

TL;DR

DeepSeek is a deep learning-based image search system that enables users to find images by describing them in natural language, leveraging semantic understanding for improved retrieval accuracy.

Contribution

It introduces a novel NLP-driven deep learning model for content-based image retrieval, integrating natural language queries with image semantic understanding.

Findings

Effective retrieval of images based on natural language descriptions

Improved semantic matching between text queries and images

Potential to enhance browsing of large multimedia datasets

Abstract

Most of the internet today is composed of digital media that includes videos and images. With pixels becoming the currency in which most transactions happen on the internet, it is becoming increasingly important to have a way of browsing through this ocean of information with relative ease. YouTube has 400 hours of video uploaded every minute and many million images are browsed on Instagram, Facebook, etc. Inspired by recent advances in the field of deep learning and success that it has gained on various problems like image captioning and, machine translation , word2vec , skip thoughts, etc, we present DeepSeek a natural language processing based deep learning model that allows users to enter a description of the kind of images that they want to search, and in response the system retrieves all the images that semantically and contextually relate to the query. Two approaches are described in the following sections.