2 posts tagged with "yolo11"

The Astra Application Challenge was designed to inspire creativity and innovation, encouraging participants to explore the full potential of Astra’s capabilities. Open to developers and innovators alike, the challenge invited participants from our Embedded World 2025: Integrate Cutting-Edge AI Features into Your Embedded Device to build impactful, real-world applications in two exciting categories leveraging Astra's NPU with YOLO models or creating advanced AI assistants integrated with IoT solutions.

🏆Astra Application Challenge Winner : Bionic Robot Hand​

Learn more about Astra Application Challenge in the Community section. After a competitive selection process, we’re thrilled to feature GRINN’s outstanding project: Bionic Robot Hand Project, an impressive blend of computer vision, embedded AI, and robotic control. Check out the code in the Grinn GitHub repository.

Object detection has seen remarkable progress with innovations like the YOLO series, a powerhouse in real-time detection tasks. With each new iteration, YOLO brings enhanced accuracy and speed, making it ideal for applications across security, autonomous vehicles, and more. In this blog, you will walk through fine-tuning YOLO11, the latest version of the YOLO family, on a custom pumpkin dataset using Roboflow, optimizing the model for Astra Machina's NPU, and running real-time video inference on Astra Machina.