DetectumTM – 10x Faster
Accuracy. It’s the same problem again and again with all open-source object detector algorithms.
And it gets worse. Because struggling to get accuracy robs you of the time needed to ensure your project’s a success.
It doesn’t have to be this way, and it won’t be when you train your AI model with Xailient’s DetectumTM algorithm. Incredibly accurate. Sensationally fast. And it’s FREE.
DetectumTM – Xailient’s industry-leading tiny single-class object detection model for Edge devices.
Xailient is a Computer Vision company specializing in putting incredibly accurate AI onto impossibly small Edge devices.
We’ve built the world’s smallest and fastest object detector to fit on extremely tiny devices running on exceptionally low power.
Specializing in TinyML computer vision for Edge devices, Xailient uses its patented technology to make embedded-edge CV accurate, real-time, and cost-effective, solving the most difficult problems in the Enterprise CV lifecycle.
Varroa mites are parasites that kill bees. When that happens, it’s not just the honey that’s in short supply. So too are flowers, plants, and crops that depend on bee pollination to propagate.
The problem. How to detect and stop tiny Varroa mites attached to bees entering their hive.
Xailient’s solution was to use incredibly accurate computer vision AI embedded on small Edge devices located at the entrance to each hive and powered by solar.
We’re proud to be trusted by the Australian Department of Agriculture to detect Varroa mites accurately.
Speed is obvious for face recognition. Faster the speed, the more instantaneous and seamless the application.
But a lot more can happen. Speed should also tie to accuracy because the more a face is processed per second, the higher the confidence of facial recognition.
So how fast is fast? Lightning-fast at 12ms or 83 fps*. That’s 83 chances in one second for a person’s face to unlock their phone.
Yep. Speed improves accuracy, but only with Xailient can you do both.
* The new MAX78000 chip
And focus on what matters. just like people do.
Today, computer vision AI works by brute force, testing thousands of random guesses to see if one matches your training data. It’s wasteful and expensive. That’s why Xailient turned to nature to find a better way.
Our vision works by identifying what matters and focusing on that. It’s a process called Selective Attention.
Xailient teaches computers to see using the strategies that evolved in nature. Use it in conjunction with your AI to drop the frames that are empty and don’t matter. Or zoom in on the parts of the field of view that do.
You’ll get insights and resources into:
Tiny Edge computing use cases.
Market trends in Edge computing.
Computer Vision AI at the Edge.
Machine learning at the Edge.