Felix Baum, Director of Product Management for AI Software at Qualcomm, presents the “Efficient Deployment of Quantized ML Models at the Edge Using Snapdragon SoCs” tutorial at the May 2019 Embedded Vision Summit. Increasingly, machine learning models are being deployed at the edge, and these models are getting bigger. As a result, we are hitting […]
Thies Möller, Technical Architect at Basler, presents the “Using Blockchain to Create Trusted Embedded Vision Systems” tutorial at the May 2019 Embedded Vision Summit. In many IoT architectures, sensor data must be passed to cloud services for further processing. Traditionally, “trusted third parties” have been used to secure this data. In this talk, Möller explores
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Sébastien Taylor, Vision Technology Architect at Au-Zone Technologies, presents the “Tools and Techniques for Optimizing DNNs on Arm-based Processors with Au-Zone’s DeepView ML Toolkit” tutorial at the May 2019 Embedded Vision Summit. In this presentation, Taylor describes methods and tools for developing, profiling and optimizing neural network solutions for deployment on Arm MCUs, CPUs and
Walter Bell, 3D Imaging Application Engineer at Infineon Technologies, presents the “REAL3 Time of Flight: A New Differentiator for Mobile Phones” tutorial at the May 2019 Embedded Vision Summit. In 2019, 3D imaging has become mainstream in mobile phone cameras. What started in 2016 with the first two smartphones using an Infineon 3D time-of-flight (ToF)
Paul Brasnett, PowerVR Business Development Director for Vision and AI at Imagination Technologies, presents the “Object Detection for Embedded Markets” tutorial at the May 2019 Embedded Vision Summit. While image classification was the breakthrough use case for deep learning-based computer vision, today it has a limited number of real-world applications. In contrast, object detection is
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Oleg Sinyavskiy, Director of Research and Development at Brain Corp, presents the “Sensory Fusion for Scalable Indoor Navigation” tutorial at the May 2019 Embedded Vision Summit. Indoor autonomous navigation requires using a variety of sensors in different modalities. Merging together RGB, depth, lidar and odometry data streams to achieve autonomous operation requires a fusion of
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Sergey Dorodnicov, Software Architect at Intel, presents the “Applied Depth Sensing with Intel RealSense” tutorial at the May 2019 Embedded Vision Summit. As robust depth cameras become more affordable, many new products will benefit from true 3D vision. This presentation highlights the benefits of depth sensing for tasks such as autonomous navigation, collision avoidance and
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Peter Zatloukal, VP of Engineering at Xnor.ai, presents the “A Self-service Platform to Deploy State-of-the-art Deep Learning Models in Under 30 Minutes” tutorial at the May 2019 Embedded Vision Summit. The first-of-its-kind, self-service platform described in this presentation makes it possible for software and hardware developers—even those who aren’t skilled in artificial intelligence—to deploy hyper-efficient,
Mehrsan Javan, CTO of Sportlogiq, presents the “Teaching Machines to See, Understand, Describe and Predict Sports Games in Real Time” tutorial at the May 2019 Embedded Vision Summit. Sports analytics is about observing, understanding and describing the game in an intelligent manner. In practice, this means designing a fully-automated, robust, end-to-end pipeline; from visual input,
David Julian, CTO and Founder of Netradyne, presents the “Addressing Corner Cases in Embedded Computer Vision Applications” tutorial at the May 2019 Embedded Vision Summit. Many embedded vision applications require solutions that are robust in the face of very diverse real-world inputs. For example, in automotive applications, vision-based safety systems may encounter unusual configurations of
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