IXEAN Mata

Using the latest research on computer vision, Ixean has developed a novel neural network system capable of matching the accuracy of much larger state-of-the-art models such as YOLOv11 and YOLOv26 in various drone target detection and tiny person detection tasks. More importantly, our model could operate purely on our CPU processing stack and still have much higher frames per second (40+FPS) than the larger benchmark models, which were already running on top-of-the-line edge GPU hardware such as the current market best, the Hailo AI Accelerator module series. So not only can we achieve the same level of performance in accuracy and even higher FPS, but we do so with less supply chain risk and hardware costs since we do not require a GPU. We also have a 2nd detection neural network model of the same architecture, but this time for the thermal vision camera. This grants us flexibility in a fire-and-forget scenario. These two together we call the IXEAN Mata system, which means Eye.  

Mata architecture neural networks can range from extremely lightweight models for the most resource-constrained of tasks to heavier but still efficient models that prioritize high accuracy. The lightweight models are suitable for smaller robotic platforms that have even more limited compute capacity or on drones that require extremely high FPS for tracking. Similarly, the larger models are suitable for demanding computer vision tasks such as multiple target detection, classification, and tracking.