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Landmine Detection

Using synthetic data to train neural networks for detecting land mines not only reduces costs and risks by eliminating the need for field testing, but also improves the ability of the AI to recognize mines amidst varying types of vegetation, enhancing detection accuracy across diverse terrains and environmental conditions.


Simulating Naval Mine Environments

Defining 3D environments for simulations of naval mines involves creating detailed and dynamic underwater models that accurately represent varying sea conditions and seabed topographies to enhance the realism and effectiveness of mine detection training. Given the usually poor underwater visibility, we simulate sonar data in addition to optical spectrum data, accounting for environmental factors such as water temperature and composition.

3D Simulations for Dynamic Environments


Generating dynamic synthetic 3D environments for naval mine use cases involves the creation of highly detailed and accurate maritime scenarios that can be used for training and testing purposes. These synthetic environments are designed to simulate a variety of underwater conditions and mine types, enabling the development and refinement of mine detection and neutralization strategies without the risks and costs associated with real-world deployments. By leveraging advanced computer graphics and procedural generation techniques, these virtual settings include realistic ocean topographies, varying water clarity, and diverse marine life, all of which are crucial for creating authentic training data.

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