To Identify the Monuments from Satellite Images Using Deep Learning

Abstract

The increasing availability of high-resolution satellite imagery and advancements in Artificial Intelligence have created new opportunities for automated monument identification and heritage monitoring. Manual identification of monuments from satellite images is a time-consuming and challenging process, especially when dealing with large-scale geographical data. Variations in image resolution, illumination, viewing angles, and surrounding environmental conditions further complicate accurate recognition. To address these challenges, this project presents an Identification of Monuments from Satellite Images Using Deep Learning system that automatically recognizes monuments from satellite imagery using a Convolutional Neural Network (CNN). The proposed system processes uploaded satellite images through image preprocessing techniques, including resizing, normalization, and feature extraction, before performing classification using a trained deep learning model. A user-friendly web application developed using the Flask framework enables secure user registration, authentication, image upload, and real-time prediction of monument names along with confidence scores. This intelligent approach minimizes manual effort, improves recognition accuracy, and provides rapid predictions for users.