Technical Insights

“New Methods for Implementation of 2-D Convolution for Convolutional Neural Networks,” a Presentation from Santa Clara University

Tokunbo Ogunfunmi, Professor of Electrical Engineering and Director of the Signal Processing Research Laboratory at Santa Clara University, presents the “New Methods for Implementation of 2-D Convolution for Convolutional Neural Networks” tutorial at the September 2020 Embedded Vision Summit. The increasing usage of convolutional neural networks (CNNs) in various applications on mobile and embedded devices […]

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“Improving Power Efficiency for Edge Inferencing with Memory Management Optimizations,” a Presentation from Samsung

Nathan Levy, Project Leader at Samsung, presents the “Improving Power Efficiency for Edge Inferencing with Memory Management Optimizations” tutorial at the September 2020 Embedded Vision Summit. In the race to power efficiency for neural network processing, optimizing memory use to reduce data traffic is critical. Many processors have a small local memory (typically SRAM) used

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“Image-Based Deep Learning for Manufacturing Fault Condition Detection,” a Presentation from Samsung

Jake Lee, Principal Engineer and Head of the Machine Learning Group at Samsung, presents the “Image-Based Deep Learning for Manufacturing Fault Condition Detection” tutorial at the September 2020 Embedded Vision Summit. In this presentation, Lee explores applying deep learning to analyzing manufacturing parameter data to detect fault conditions. The manufacturing parameter data contains multivariate time

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“Using an ISP for Real-time Data Augmentation,” a Presentation from Pony.AI

Timofey Uvarov, Camera System Lead at Pony.AI, presents the “Using an ISP for Real-time Data Augmentation” tutorial at the September 2020 Embedded Vision Summit. Image signal processors (ISPs) are tasked with processing raw pixels delivered by image sensors in order to optimize the quality of images. In computer vision applications, much attention is focused on

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“Introduction to the TVM Open Source Deep Learning Compiler Stack,” a Presentation from the University of Washington

Luis Ceze, a Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, co-founder and CEO of OctoML, and Venture Partner at Madrona Venture Group, presents the “Introduction to the TVM Open Source Deep Learning Compiler Stack” tutorial at the September 2020 Embedded Vision Summit. There is an

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“Imaging Systems for Applied Reinforcement Learning Control,” a Presentation from Nanotronics

Damas Limoge, Senior R&D Engineer at Nanotronics, presents the “Imaging Systems for Applied Reinforcement Learning Control” tutorial at the September 2020 Embedded Vision Summit. Reinforcement learning has generated human-level decision-making strategies in highly complex game scenarios. But most industries, such as manufacturing, have not seen impressive results from the application of these algorithms, belying the

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“MLPerf: An Industry Standard Performance Benchmark Suite for Machine Learning,” a Presentation from Facebook and Arizona State University

Carole-Jean Wu, Research Scientist at Facebook AI Research and an Associate Professor at Arizona State University, presents the “MLPerf: An Industry Standard Performance Benchmark Suite for Machine Learning” tutorial at the September 2020 Embedded Vision Summit. The rapid growth in the use of DNNs has spurred the development of numerous specialized processor architectures and software

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“Khronos Standard APIs for Accelerating Vision and Inferencing,” a Presentation from the Khronos Group

Neil Trevett, President of the Khronos Group and Vice President of Developer Ecosystems at NVIDIA, presents the “Khronos Standard APIs for Accelerating Vision and Inferencing” tutorial at the September 2020 Embedded Vision Summit. The landscape of processors and tools for accelerating inferencing and vision applications continues to evolve rapidly. Khronos standards, such as OpenCL, OpenVX,

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“Feeding the World Through Embedded Vision,” a Presentation from John Deere

Travis Davis, Delivery Manager for the Automation Delivery team with the Intelligent Solutions Group at John Deere, presents the “Feeding the World Through Embedded Vision” tutorial at the September 2020 Embedded Vision Summit. Although it’s not widely known outside of the industry, computer vision is beginning to be used at scale in agriculture, where it

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“Challenges and Approaches for Cascaded DNNs: A Case Study of Face Detection for Face Verification,” a Presentation from Imagination Technologies

Ana Salazar, Senior Research Manager at Imagination Technologies, presents the “Challenges and Approaches for Cascaded DNNs: A Case Study of Face Detection for Face Verification” tutorial at the September 2020 Embedded Vision Summit. This talk explores the challenges of deploying serial computer vision tasks implemented with DNNs. Neural network accelerators have demonstrated significant gains in

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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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