Intel & Edge AI for Retail

Part 1: Deploying Accelerated Computer Vision for Retail Applications: Join us for a two-hour session in which Intel experts will take you through advanced topics in accelerating computer vision. We will walk you through deploying your deep learning application using the OpenVINO toolkit, starting with a trained model from Caffe, Tensorflow or ONNX and creating efficient implementations on different Intel hardware accelerators: CPUs, integrated GPUs, FPGAs ad the Movidius Neural Compute Stick.

Part 2: DevCloud and Demos: Intel DevCloud for the Edge is a free cloud resource offering a wide range of software tools and pre-configured Intel hardware to enable remote development and testing of deep learning applications. In this one-hour session, we will build on what we learned in Part 1 and use DevCloud to show live demonstrations of benchmarking various trained models executing on specific devices using the Deep Learning Workbench. We will highlight the wide range of retail examples available in the Intel DevCloud for the Edge, including store aisle monitoring, multi-camera store traffic monitoring, and shopper gaze detection. We’ll also introduce tutorials for encrypted models, how to migrate from DevCloud to a local edge device, and DL Streamer Pipeline examples. (DL Streamer is an easy way to construct media analytics pipelines using OpenVINO. It leverages the Gstreamer open source media framework.)

Part 3: Get a DevCloud Account: In this final, hands-on session, developers will receive a code for 30 days of access to the Intel DevCloud for the Edge, followed by a quick review of the demos highlighted in Part 2 of this class. Intel team members will be on hand to guide attendees as they begin to explore the different hardware and software options available in the DevCloud.

Who should attend?
AI application developers with existing or planned systems that can benefit from increased performance and efficiency.

Date/Time: Monday, September 21 – 9:00 am – 1:30 pm

Cost: $2