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 […]
This blog post was originally published at Lattice Semiconductor’s website. It is reprinted here with the permission of Lattice Semiconductor. If you were to ask them (and I have), you would discover that many people think of radar in the context of things like airplanes and ships and the evening weather forecast on TV. As
Lattice FPGAs Power Real-Time Radar Adapter Cards Read More +
On March 25, 2021 at 9 am PT (noon ET), Diptesh Nandi, Product Marketing Manager in the FPGA Business Unit at Microchip Technology, will present the free half-hour webinar “Enabling Small Form Factor, Anti-tamper, High-reliability, Fanless Artificial Intelligence and Machine Learning,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event
This technical article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. AI workflows are complex. Building an AI application is no trivial task, as it takes various stakeholders with domain expertise to develop and deploy the application at scale. Data scientists and developers need easy access to software
Building and Deploying a Face Mask Detection Application Using NGC Collections Read More +
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
“Using an ISP for Real-time Data Augmentation,” a Presentation from Pony.AI Read More +
This market research report was originally published at Yole Développement’s website. It is reprinted here with the permission of Yole Développement. Yole Développement (Yole) has been monitoring the trajectories of Advanced Driver Assist (ADAS) and Autonomous Vehicle (AV) players for many years and has recently published Sensing and computing for ADAS 2020 and Sensors for
CES 2021 – The More than Moore Pivot from Intel Mobileye Read More +
On March 11, 2021 at 9 am PT (noon ET), Christian Graber, Director of Platform Architecture at GrAI Matter Labs, will present the free half-hour webinar “Brain-inspired Processing Architecture Delivers High Performance, Energy-efficient, Cost-effective AI,” organized by the Edge AI and Vision Alliance. Here’s the description, from the event registration page: If a picture is
Free Webinar Explores High Performance, Energy-efficient, Cost-effective AI Processing Read More +
This blog post was originally published at Ambarella’s website. It is reprinted here with the permission of Ambarella. Advances in our HDR processing algorithms are changing the way cameras handle challenging lighting conditions. In everyday life we often encounter strong lighting contrasts—shadows under the sun, bright lamps at night, a garage door opening to reveal
New Heights for High Dynamic Range Read More +
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
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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