Smarter AI starts with better data
Real-world training data is scarce, expensive, and often too narrow to cover the complexity of real deployment scenarios. FUSION ( Framework for Unified Synthetic Image generatiON) is our synthetic data generation engine, capable of producing both RGB and thermal datasets. From just a handful of real samples, FUSION creates hundreds of controlled variations, giving AI models the diversity they need to learn faster and generalize better.
Our Results
- Generated ~750 synthetic frames with 75 variations from just 2 initial real observations.
- Trained on a YOLO12-small base model to quantify the impact of synthetic augmentation.
- Tested against a dataset of 17 unseen real-world variations.
- Achieved a +38 percentage point F1 improvement (23% → 61%) in balanced detection accuracy.
With FUSION, synthetic data isn’t just a substitute – it’s a measurable performance accelerator.
Dataset Examples
Our goal is to showcase a developing technology for synthetic data generation. The datasets are a first step, and we plan to maintain and expand them over time as our methods improve.
Synthetic Landmine Dataset (Experimental)
Built on inert landmine observations, AETHER captures the subtle thermal and spatial signatures of PFM-1 mines. Scarce samples are expanded into hundreds of unique scenarios, enabling safe and scalable model training without field risks.
FPV Drone Dataset
From a single FPV drone, FUSION generated a dataset that captures both its visual and thermal footprint across diverse contexts. This supports robust detection systems for aerial threats, with coverage across lighting conditions, angles, and backgrounds.
Ready to Integrate
We’re actively seeking partners to pilot FUSION. Our team supports data collection, synthetic dataset generation, and seamless integration into AI pipelines. Whether the challenge is safety, scarcity, or scale, FUSION delivers the data you need to accelerate your models.