Vinod Kathail, Fellow and Chief Architect at Xilinx, presents the “Vitis and Vitis AI: Application Acceleration from Cloud to Edge” tutorial at the September 2020 Embedded Vision Summit. Xilinx SoCs and FPGAs provide significant advantages in throughput, latency, and energy efficiency for production deployments of compute-intensive applications when compared to CPUs and GPUs. Over the […]
Manisha Agrawal, Product Marketing Engineer at Texas Instruments, presents the “Making Edge AI Inference Programming Easier and Flexible” tutorial at the September 2020 Embedded Vision Summit. Deploying an AI model at the edge doesn’t have to be challenging—but it often is. Embedded processing vendors have unique sets of software tools for deploying models. It takes
Dr. Satya Mallick, CEO of OpenCV.org and OpenCV.ai, presents the “OpenCV: Rapid Growth and Evolution Beyond the Library” tutorial at the September 2020 Embedded Vision Summit. The last 20 years of OpenCV were dedicated to building the world’s largest high-performance computer vision library. Now, the organization is fast expanding beyond the flagship library to better
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Jack Erickson, Principal Product Marketing Manager at MathWorks, presents the “Deploying Deep Learning Applications on FPGAs with MATLAB” tutorial at the September 2020 Embedded Vision Summit. Designing deep learning networks for embedded devices is challenging because of processing and memory resource constraints. FPGAs present an even greater challenge due to the complexity of programming in
Carsten Traupe, Director of Product Management at IDS Imaging Development Systems, presents the “How to Create Your Own AI-Enabled Camera Solution in Days” tutorial at the September 2020 Embedded Vision Summit. Cameras coupled with AI can solve numerous real-world problems. But developing an AI camera solution can be a complex and time-consuming undertaking, especially for
Orr Danon, Founder and CEO of Hailo, presents the “Lessons Learned from the Deployment of Deep Learning Applications In Edge Devices” tutorial at the September 2020 Embedded Vision Summit. Edge applications have tough, widely varying requirements. Danon shares lessons learned from three real-world applications in which Hailo’s deep learning processor is being used to implement
Rami Drucker, Machine Learning System Team Leader at CEVA, presents the “Memory Allocation in AI and Computer Vision Applications” tutorial at the September 2020 Embedded Vision Summit. Efficient edge computing is the foundation underlying AI and computer vision applications in autonomous vehicles, cameras, drones and many other applications. Because deep neural networks (DNNs) are memory
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Felix Heide, Co-Founder and Chief Technology Officer at Algolux, presents the “Designing Cameras to Detect the “Invisible”: Handling Edge Cases Without Supervision” tutorial at the September 2020 Embedded Vision Summit. Vision systems play an essential role in safety-critical applications, such as advanced driver assistance systems, autonomous vehicles, video security, and fleet management. However, today’s imaging
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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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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