AI powered Satellite Image Forgery Detection

The AI Satellite Image Forgery Detection project aims to develop a web application that utilizes advanced machine learning techniques to identify and verify the authenticity of satellite images. With the increasing use of satellite imagery in various industries, the need to detect forged or manipulated images has become crucial for ensuring data integrity and accuracy.

The project leverages AI-based image processing algorithms such as Convolutional Neural Networks (CNNs) to analyze satellite images and detect anomalies, inconsistencies, or signs of manipulation. The application uses a combination of supervised and unsupervised learning techniques to train the model on a large dataset of authentic and altered satellite images.

Key Features:
Forgery Detection: Identifies altered satellite images based on patterns in the data.

Image Comparison: Compares satellite images against a database of verified images.

Real-Time Analysis: Allows users to upload images for immediate analysis.

Reporting: Generates a detailed report on whether the image is authentic or forged.
Impact:
This project aims to enhance the accuracy and trustworthiness of satellite image data used in environmental monitoring, defense, and disaster response, ensuring that users can make informed decisions based on reliable satellite imagery.

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