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Delivering Performance Promise for Convolutional Neural Networks Across Full Range of Intel® Hardware


Description

Intel has recently entered the Computer Vision and Deep Learning domain with its OpenVINO® solution. It’s important to understand the performance aspects and other productization challenges of using Convolutional Neural Networks (CNNs) with Intel® technology-based hardware, and how OpenVINO solved them.

In this session, you’ll learn how CNNs are executed on such varied target environments as low-power, always-on embedded platforms or full-blown servers. Deploying CNNs is challenging, as the end target environment typically look very different from the training environment. Training is typically done on high-end data centers, using popular training frameworks such as Caffe* and TensorFlow. Scoring (inference), in contrast, can take place on embedded devices or accelerators like FPGA.

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