Train your model to detect drones reliably, regardless of lighting, clutter, and weather conditions.
Adding synthetic datasets lets you train on more lighting conditions, backgrounds, camera angles, and flight behaviors, making drone detection more reliable in real missions.
Results achieved
Choose a mission scene from the catalogue or request a custom one. Add other assets (e.g., birds) into the scene to teach your model to differentiate drones from other objects and reduce false positives in drone detection.
Train your model to recognize the most widely used rotary and fixed-wing drones from our annotated list or have new ones added in a couple of days. Position up to 10 drones at varying distances and speeds to improve detection in fast or converging flights.
Alter illumination, time of day, and weather so your model can reliably detect drones at dusk, dawn, night, and in bright glare.
Set up how your model “sees” drones. Select camera types (fisheye, pinhole), horizontal field of view, rotation, and perspective (ground-to-air, air-to-air) to match actual scenarios and improve sim-to-real performance.
Render and export fully annotated datasets ready for your drone detection pipeline.
Your virtual model precisely replicates real-world camera effects, including chromatic aberration, ISO noise, and Gaussian blur.
The synthetic data you get matches daytime-dependent light and shadow changes, so models detect drones in any lighting.
Forget about annotation noise. Get automatically generated, pixel-perfect segmentations, semantic masks, and 3D bounding boxes with consistent accuracy.
No limits on training settings. Randomize parameters and generate datasets covering any variety of conditions and edge cases.
Configure every element of a mission scenario, from layout to camera settings, in minutes, not days or weeks, with an easy-to-use blueprint.
Generating 5,000 high-fidelity frames takes only 8 hours. Need it faster? Add more compute through our Platform, no setup or backend work on your side.
Director Core ML, Google. Ex-Nvidia
My team and I take a great pleasure in supporting SKY ENGINE AI, our collaboration is a win-win for both Nvidia and SKY ENGINE AI. SKY ENGINE showing what is possible with Nvidia tech and SKY ENGINE AI is leading the way with synthetic data and ML platform, which ultimately will dominate how the companies train DL models. I look forward to more collaboration opportunities.
We’re always happy to share performance metrics showing how well it works in real-world scenarios, just contact our sales team to learn more. You can also download a free dataset and test it in your drone detection pipeline to see the results for yourself.
If you can’t find the scenario elements you need, reach out and we’ll add them. The Synthetic Data Cloud can simulate any background, camera setting, or drone model, so we can deliver exactly what you need in a short time.
Currently, we provide our renders for drone detection in RGB. We’re working on adding more modalities, like infrared and thermal, building on what we’ve already delivered in other industries.
We offer two options. First, our team can generate datasets for you according to your specs under an NDA. Second, you can access the Synthetic Data Cloud yourself and create the datasets. Your instance stays private, and we never have access to your data.
