How Machine Learning is Enabling New Smart Camera Applications

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Presented by

Dylan Zika, Product Manager, Arm

About this talk

Smart Cameras is one of the fastest growing areas of Machine Learning. Join Arm for a live webinar to hear how smart cameras are being redefined by AI and ML workloads. Today many camera systems still rely on human visual inspection to detect, recognize and track objects of interest. While this is cost effective for single cameras systems, enabling Automatic inspections will lower cost in large scale environments. AI algorithms complement a single person’s ability, focusing human inspection on the most critical, camera video streams. Key ML algorithms enabling automatic inspection are object detection, and image segmentation to locate, track, and create boundaries. Future systems are increasing security and intelligence with emerging algorithms like human pose estimation or enabling voice interfaces on the camera. Dylan Zilka from Arm’s Machine Learning Group will show you how to analyze ML models and give guidance on understanding ML system design and requirements for your products. Dylan holds a Masters (MSEE) in Computer Architecture from The University of Texas at Austin, with a technical emphasis on software use-cases and hardware design. His technical Master's was supported with key MBA foundations in Entrepreneurship, Marketing, and Technology Strategy. Dylan’s passion for technologies is broad, with talents spanning hardware, software, and business strategy. This webinar will cover: • Showcase multiple ML smart camera use cases • Learn how to analyze ML models • Guidance on how to better understand ML system design/ML requirements for their products

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