An Enhanced Image Loading Framework for Social Media Applications

Abstract

Online Social network (OSN) is the most popular platform where users prefer to share images and videos. Image loading time in social media applications is time-consuming due to significantly less internet bandwidth. Uploading an image on a social media platform demands accurate size, highest quality, format, and resolution. Often, duplicates of images may be uploaded by the user accidentally. Uploading images or videos by individual users on platforms like Facebook or Instagram is Content loading. In this article, we suggest a suitable method for reducing the content loading time by finding the duplicate images and replacing those images with the original image that is already loaded using ANNOY (Artificial Neural Network Oh Yeah). In the methodology we could successfully reduce the image loading time by checking the duplication.