Brian Dipert

“Implementing an Optimized CNN Traffic Sign Recognition Solution,” a Presentation from NXP Semiconductors and Au-Zone Technologies

Algorithms & Models, Au-Zone Technologies, Automotive, NXP Semiconductors, Object Identification, Optical Character Recognition, Processors, Software, Tools, Videos /

Rafal Malewski, Head of the Graphics Technology Engineering Center at NXP Semiconductors, and Sébastien Taylor, Vision Technology Architect at Au-Zone Technologies, present the "Implementing an Optimized CNN Traffic Sign Recognition Solution" tutorial at the May 2017 Embedded Vision Summit. Now that the benefits of using deep neural networks for image classification are well known, the […]

“Implementing an Optimized CNN Traffic Sign Recognition Solution,” a Presentation from NXP Semiconductors and Au-Zone Technologies Read More +

“Implementing an Optimized CNN Traffic Sign Recognition Solution,” a Presentation from NXP Semiconductors and Au-Zone Technologies

Algorithms & Models, Au-Zone Technologies, Automotive, NXP Semiconductors, Object Identification, Optical Character Recognition, Processors, Software, Tools, Videos /

Rafal Malewski, Head of the Graphics Technology Engineering Center at NXP Semiconductors, and Sébastien Taylor, Vision Technology Architect at Au-Zone Technologies, present the "Implementing an Optimized CNN Traffic Sign Recognition Solution" tutorial at the May 2017 Embedded Vision Summit. Now that the benefits of using deep neural networks for image classification are well known, the

“Implementing an Optimized CNN Traffic Sign Recognition Solution,” a Presentation from NXP Semiconductors and Au-Zone Technologies Read More +

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Privacy in the Era of Ubiquitous Cameras and AI

Blog Posts, Privacy /

This blog post was originally published in the late July 2017 edition of BDTI’s InsideDSP newsletter. It is reprinted here with the permission of BDTI. Lately I’ve been thinking about the relationship between embedded vision and privacy. Surveillance cameras are nothing new, of course. For decades, they’ve been ubiquitous in and around restaurants, stores, banks,

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Movidius Low-power VPU Technology Delivers 4K VR Pixel-processing Performance for Motorola’s Newest Moto Mod

Uncategorized /

25 July 2017 – Movidius’ Myriad 2 Vision Processing Unit (VPU) technology, known for its image signal processing and computer vision capabilities with high energy efficiency, was selected by Motorola Mobility to power their newest Moto Mod: the 360 Camera. Moto Mods are unique modular accessories for Motorola smartphones that bring advanced functionality beyond traditional

Movidius Low-power VPU Technology Delivers 4K VR Pixel-processing Performance for Motorola’s Newest Moto Mod Read More +

“Deep Learning Beyond Cats and Cars: Developing a Real-life DNN-based Embedded Vision Product for Agriculture, Construction, Medical, or Retail,” a Presentation from Luxoft

Algorithms & Models, LUXOFT, Processors, Sensors and Cameras, Software, Tools, Videos /

Alexey Rybakov, Senior Director for Embedded Systems at Luxoft, presents the "Deep Learning Beyond Cats and Cars: Developing a Real-life DNN-based Embedded Vision Product for Agriculture, Construction, Medical, or Retail" tutorial at the May 2017 Embedded Vision Summit. By now we know very well how to design and train a neural network to recognize cats,

“Deep Learning Beyond Cats and Cars: Developing a Real-life DNN-based Embedded Vision Product for Agriculture, Construction, Medical, or Retail,” a Presentation from Luxoft Read More +

“Deep Learning Beyond Cats and Cars: Developing a Real-life DNN-based Embedded Vision Product for Agriculture, Construction, Medical, or Retail,” a Presentation from Luxoft

Algorithms & Models, LUXOFT, Processors, Sensors and Cameras, Software, Tools, Videos /

Alexey Rybakov, Senior Director for Embedded Systems at Luxoft, presents the "Deep Learning Beyond Cats and Cars: Developing a Real-life DNN-based Embedded Vision Product for Agriculture, Construction, Medical, or Retail" tutorial at the May 2017 Embedded Vision Summit. By now we know very well how to design and train a neural network to recognize cats,

“Deep Learning Beyond Cats and Cars: Developing a Real-life DNN-based Embedded Vision Product for Agriculture, Construction, Medical, or Retail,” a Presentation from Luxoft Read More +

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BrainChip Adds Thomas Stengel as Vice President of Americas Business Development

BrainChip, News /

Leadership Team in Place to Drive Sales of new AI-Based BrainChip Studio Video Analytic Solutions Highlights: Tom Stengel joins as VP of Business Development for the Americas as the Company launches BrainChip Studio, a commercially available integrated software suite for pattern and facial recognition analytics. BrainChip expands its sales organization with a 30-year industry veteran

BrainChip Adds Thomas Stengel as Vice President of Americas Business Development Read More +

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Snapdragon Neural Processing Engine Now Available on Qualcomm Developer Network

News /

Designed to Fuel On-device Artificial Intelligence Through Developers and Manufacturers Jul 25, 2017 – San Diego – Qualcomm Technologies, Inc., a subsidiary of Qualcomm Incorporated (NASDAQ: QCOM), announced today the immediate availability of the Qualcomm® Snapdragon™ Neural Processing Engine (NPE) software development kit (SDK) on Qualcomm Developer Network. The Snapdragon NPE is the first deep

Snapdragon Neural Processing Engine Now Available on Qualcomm Developer Network Read More +

“What is an Embedded Vision Processor?,” a Video from Synopsys

Videos /

This video, one in a series published by Alliance member company Synopsys, explains what is included in embedded vision processors, the features and functions that they provide, and the tools designers use for implementation. The video also compares (from Synopsys' perspective) embedded vision processors to GPUs, DSPs, and FPGAs.

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JetPack 3.1 Doubles Jetson’s Low-Latency Inference Performance

Uncategorized /

Today, NVIDIA released JetPack 3.1, the production Linux software release for Jetson TX1 and TX2. With upgrades to TensorRT 2.1 and cuDNN 6.0, JetPack 3.1 delivers up to a 2x increase in deep learning inference performance for real-time applications like vision-guided navigation and motion control, which benefit from accelerated batch size 1. The improved features

JetPack 3.1 Doubles Jetson’s Low-Latency Inference Performance Read More +

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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