Enabling Technologies

“Enabling Embedded AI for Healthcare,” a Presentation from VeriSilicon

Shang-Hung Lin, Vice President of Machine Learning and Neural Processor Product Development at VeriSilicon, presents the “Enabling Embedded AI for Healthcare” tutorial at the September 2020 Embedded Vision Summit. Wearable electronics have started to become part of our daily lives, in the form of watches, wristbands, fitness trackers and the like. Advances in sensor design […]

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“Advancing Embedded Vision for an Autonomous World,” a Presentation from Qualcomm

Ning Bi, Vice President of Technology at Qualcomm, presents the “Advancing Embedded Vision for an Autonomous World” tutorial at the September 2020 Embedded Vision Summit. Qualcomm Technologies Inc. has revolutionized smartphones, wearables, PCs, smart homes and more. Now Qualcomm has set its sights on vehicles with solutions leveraging Qualcomm’s 5G connectivity, Qualcomm Computer Vision and

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“Benchmarking vs. Benchmarketing: Why Should You Care?,” a Presentation from Qualcomm

Felix Baum, Director of Product Management at Qualcomm, presents the “Benchmarking vs. Benchmarketing: Why Should You Care?” tutorial at the September 2020 Embedded Vision Summit. Qualcomm is determined to provide best in class AI hardware solutions, enabling companies to leverage AI acceleration in their products. But how can developers know what is the best hardware

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“Qualcomm AI Leading the Way with Distributed Intelligence,” a Presentation from Qualcomm

Ziad Asghar, Vice President of Product Management at Qualcomm, presents the “Qualcomm AI Leading the Way with Distributed Intelligence” tutorial at the September 2020 Embedded Vision Summit. Qualcomm is leading the way in distributed intelligence. The company’s vision is to make all devices increasingly intelligent, giving them the ability to perceive their surroundings, to reason

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“Ergo: Perceive’s Chip – Data Center-Class Inference in Edge Devices at Ultra-Low Power,” a Presentation from Perceive

Steve Teig, CEO of Perceive, presents the “Ergo: Perceive’s Chip – Data Center-Class Inference in Edge Devices at Ultra-Low Power” tutorial at the September 2020 Embedded Vision Summit. To date, people seeking to deploy machine learning-based inference within consumer electronics have had only two choices, both unattractive. The first option entails transmitting voluminous raw data,

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“Machine-Learning-Based Perception on a Tiny, Low-Power FPGA,” a Presentation from Lattice Semiconductor

Hoon Choi, Fellow at Lattice Semiconductor, presents the “Machine-Learning-Based Perception on a Tiny, Low-Power FPGA” tutorial at the September 2020 Embedded Vision Summit. In this tutorial, Choi presents a set of machine-learning-based perception solutions that his company implemented on a tiny (5.4 mm2 package), low-power FPGA. These solutions include hand gesture classification, human detection and

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“Cadence Tensilica Edge AI Processor IP Solutions for Broad Market Use Cases,” a Presentation from Cadence

Pulin Desai, Vision and AI Product Marketing Group Director at Cadence, presents the “Cadence Tensilica Edge AI Processor IP Solutions for Broad Market Use Cases” tutorial at the September 2020 Embedded Vision Summit. In this talk, Desai presents the full range of Cadence Tensilica edge AI processing solutions. These silicon IP-based solutions serve markets from

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“Smarter Manufacturing with Intel’s Deep Learning-Based Machine Vision,” a Presentation from Intel

Tara K. Thimmanaik, Solutions Architect at Intel, presents the “Smarter Manufacturing with Intel’s Deep Learning-Based Machine Vision” tutorial at the September 2020 Embedded Vision Summit. As demand for smarter and more efficient manufacturing is growing, IoT technologies⁠—including sensors, edge devices, gateways, servers and the cloud⁠—are being used throughout the factory to compute deep learning analytics

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“Acceleration of Deep Learning Using OpenVINO: 3D Seismic Case Study,” a Presentation from Intel

Manas Pathak, Global AI Lead for Oil and Gas at Intel, presents the “Acceleration of Deep Learning Using OpenVINO: 3D Seismic Case Study” tutorial at the September 2020 Embedded Vision Summit. The use of deep learning for automatic seismic data interpretation is gaining the attention of many researchers across the oil and gas industry. The

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“Federated Edge Computing System Architectures,” a Presentation from Intel

Vaidyanathan Krishnamoorthy, Edge Inference Solutions Architect at Intel, presents the “Federated Edge Computing System Architectures” tutorial at the September 2020 Embedded Vision Summit. With ever-increasing amounts of video and other sensor data, and growing requirements for privacy and low latency, inferencing at the edge is increasingly attractive. But there are many ways to allocate and

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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