Evaluation of autoencoder for CBIR system in deep learning
Aashay Pawar · 2020
In this world of growing Internet, the number of web search queries count per day has reached more than 5 Billion as of the year 2020. Growing numbers could also indicate previous unsatisfactory results or a lack of proper language used by the user. Language is never a barrier on the Internet, but sometimes searches related to photos and images are not correctly indexed. Image-based search engines were discovered to solve this problem. Through this work, we extend the Content-Based Image Retrieval (CBIR) system by developing and evaluating a Deep Learning approach by making use of an Autoencoder for quicker and relevant results.