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26 - 28 February 2019 // Nuremberg, Germany

Conferences and supporting programme

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Session 8.2: Intelligent Systems II Hardware

Driving Deep Learning Performance Through Hardware Accelerators and Advanced Storage Technology Vortragssprache Englisch

Deep learning (DL)-based video analytics are becoming ever more effective and accurate in recent years. Streamlining custom manufacturing, city congestion, increasing physical security threat mitigation needs and improved shopping experiences are all drivers that lead to this technology being applied to a widening range of applications. Most notably these include video surveillance, industrial autonomous robotics, smart retail, etc. In order to broaden the usability of DL solution everywhere, it is necessary to empower all edge devices to be able to perform DL inferencing tasks, and utilize low power add-in cards (rather than external GPUs). This ensures DL usage can be deployed in edge, embedded and industrial applications. In this presentation, we are going to introduce a software framework called Intel® OpenVINO. We will provide detailed in-depth insight into how to use FPGA-based deep learning accelerators and Intel® Optane disks in conjunction with Intel® OpenVino, that allows developers to deploy DL workloads to a wide ranges of devices (from edge to cloud). In addition we will walk through a real world face detection and facial recognition demo to showcase the performances that edge devices could provide In this Use case solution, there are three different setups being used for three different functional stages: Face Detection, Face Feature Extraction and Face Matching

--- Date: 26.02.2019 Time: 5:00 PM - 5:30 PM Location: Conference Counter NCC Ost

Speakers

man

Muhammad Waqas Sadiq Jutt

Intel Corporation

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