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Neural Network on Minized - Number recognition
• Deep learning capability on low-end device XC7Z007s
• Multilayer Perceptron (MLP) network topology
• Extreme quantized network using Binarized Neural Networks*
• 95.8% accuracy on MNIST
• Small Fully Connected Layer: 256 nodes
• Jupyter notebook over built-in Wifi
• 91%/66% (LUT/FF) Resource Utilization
* Yaman, “FINN: A Framework for Fast, Scalable Binarized Neural
Network Inference”
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Xilinx Announces the Acquisition of DeePhi Tech
Deal to Accelerate Data Center and Intelligent Edge Applications.
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Daimler AG Selects Xilinx to Drive Artificial Intelligence-Based Automotive Applications
Xilinx and Daimler to Develop Ultra-Efficient AI Solutions for Future Mercedes-Benz Models.
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XDF (Xilinx Developer Forum)
Through connect, learn and share, XDF connects software developers and system designers to the deep expertise of Xilinx engineers, partners, and industry leaders.
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Sensor Fusion for ADAS using Xilinx reVISION Software Stack
Avnet demonstrates Multi-camera FMC, Ultra96 Advanced Image Classification and BNN on MiniZed demo in this Expo.
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Xilinx ML Suite
The Xilinx ML Suite enables developers to optimize and deploy accelerated ML inference.
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Avnet UltraZed-EV Development Kit
Consists of the UltraZed-EV SOM and Carrier Card bundled to provide a complete system for prototyping and evaluating systems based on the Xilinx MPSoC-EV device family.
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