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Market research estimates there will be as many as 20 billion connected devices in the market by 2020. These devices are expected to generate billions of petabytes of data traffic between cloud and edge devices. In 2017 alone, 8.4B connected devices are expected in the market which is sparking a strong need to pre-process data at the edge. This has led many IoT device manufacturers, especially those working on vision based devices like smart cameras, drones, robots, AR/VR, etc., to bring intelligence to the edge.
In this challenge you will be fine-tuning Convolutional Neural Networks (CNNs) that are targeted for embedded applications. Contestants are expected to leverage the Neural Compute SDK's mvNCProfile tool to analyze the bandwidth, execution time and complexity of their network at each layer, and tune it to get the best accuracy, execution time and power-efficiency.
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