TECHNOLOGIES

Object Recognition: 3 Things You Need to Know

This article was originally published at MathWorks’ website. It is reprinted here with the permission of MathWorks. What Is Object Recognition? Object recognition is a computer vision technique for identifying objects in images or videos. Object recognition is a key output of deep learning and machine learning algorithms. When humans look at a photograph or […]

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Accelerating WinML and NVIDIA Tensor Cores

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Every year, clever researchers introduce ever more complex and interesting deep learning models to the world. There is of course a big difference between a model that works as a nice demo in isolation and a model that

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Machine Vision: MVTec Presents New and Optimized Features with HALCON 20.05

Rapid access to product improvements, thanks to short release cycles Deep learning training right on the CPU To be released on May 20, 2020 Munich, April 08, 2020 – MVTec Software GmbH (www.mvtec.com), the leading international provider of machine vision software, will launch a new Progress release of its standard software HALCON on May 20, 2020.

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CEVA Announces Industry’s First High Performance Sensor Hub DSP Architecture

SensPro™ family serves as hub for processing and fusing of data from multiple sensors including camera, Radar, LiDAR, Time-of-Flight, microphones and inertial measurement units Highly-configurable and self-contained architecture brings together scalar and parallel processing for floating point and integer data types, as well as deep learning training and inferencing MOUNTAIN VIEW, Calif., – April 7,

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Robot Senses: Robots That Can See, Hear, Feel, and More

This market research report was originally published at Omdia | Tractica’s website. It is reprinted here with the permission of Omdia | Tractica. A robot with no way to sense its position or environment is simply an automaton that performs movements blindly. That is changing due to a trend toward adding vision, torque, and other

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BrainChip Introduces Company’s Event-Based Neural-Network IP and NSoC Device at Linley Processor Virtual Conference

AKD1000 is the first event-based processor for Edge AI with ultra-low power consumption and continuous learning APRIL 2, 2020–SAN FRANCISCO–(BUSINESS WIRE)– BrainChip Holdings Ltd. (ASX: BRN), a leading provider of ultra-low power, high performance edge AI technology, today announced that it will be introducing its AKD1000 to audiences at the Linley Fall Processor Virtual Conference

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Speeding Up Deep Learning Inference Using TensorFlow, ONNX, and TensorRT

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Starting with TensorRT 7.0,  the Universal Framework Format (UFF) is being deprecated. In this post, you learn how to deploy TensorFlow trained deep learning models using the new TensorFlow-ONNX-TensorRT workflow. Figure 1 shows the high-level workflow of TensorRT.

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Application Processor Unit (APU) Quarterly Market Monitor

Application processor: All-in-one solution for the computing challenges of the next decade MARKET DYNAMICS: 2019 APU market closed with total revenue of $31B. Seasonally weak Q1-20 expected to remain above $7B even as COVID-19 stresses the supply chain. Cost & ASP declines at ~20% per year through 2021; slowing to ~10% per year for 2022+.

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“OpenCV: Past, Present and Future,” a Presentation from OpenCV.org

Gary Bradski, the President and CEO of OpenCV.org, delivers the presentation “OpenCV: Past, Present and Future” at the Edge AI and Vision Alliance’s March 2020 Vision Industry and Technology Forum. Bradski shares the latest developments in the OpenCV open source library for computer vision and deep learning applications, as well as where OpenCV is heading.

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Maximize CPU Inference Performance with Improved Threads and Memory Management in Intel Distribution of OpenVINO Toolkit

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. The popularity of convolutional neural network (CNN) models and the ubiquity of CPUs means that better inference performance can deliver significant gains to a larger number of users than ever before. As multi-core processors become the norm,

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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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