Charles
Gun detection is one of the most complex challenges in computer vision for security. Firearms can appear in countless positions and environments, often partially obscured or blending into a scene.
Delivering consistent performance under those conditions requires more than adding a feature to a broader platform. It demands sustained attention to how models are trained, how data is generated, and how unique cases are identified and addressed.
At ZeroEyes, we generate our own training data intentionally and don’t rely on customer footage. This helps avoid bias toward specific environments and supports generalization across different facilities and camera setups. We also create targeted scenarios that reflect difficult, real-world conditions so the system learns to perform where it matters most.
