NXP Semiconductors

NXP Semiconductors Demonstration of Deep Learning-based Multi-object Detection Using S32V234 Vision Processor

NXP Semiconductors, Summit 2018, Videos /

Ali Osman Ors, Director of AI Strategy and Partnerships for Automotive at NXP Semiconductors, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Ors demonstrates deep learning-based multi-object detection based on MobileNet and Single Shot Detector (SSD) running in real-time on the embedded automotive-grade S32V234 Vision SoC, with the capability of detecting […]

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NXP Semiconductors Demonstration of Optimized Performance and Memory Utilization for Object Detection on i.MX RT

NXP Semiconductors, Summit 2018, Videos /

Markus Levy, Director of Enabling Technologies at NXP Semiconductors, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Levy demonstrates the i.MX RT architecture, which represents the convergence of low-power application processors and high-performance microcontrollers. This particular demo shows the i.MX RT1050 MCU, which is based on a 600MHz Arm® Cortex®-M7 core

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“Understanding Automotive Radar: Present and Future,” a Presentation from NXP Semiconductors

Algorithms, Automotive, Edge AI and Vision Alliance, NXP Semiconductors, Processors, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Arunesh Roy, Radar Algorithms Architect at NXP Semiconductors, presents the “Understanding Automotive Radar: Present and Future” tutorial at the May 2018 Embedded Vision Summit. Thanks to its proven, all-weather range detection capability, radar is increasingly used for driver assistance functions such as automatic emergency braking and adaptive cruise control. Radar is considered a crucial sensing

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“The Role of the Cloud in Autonomous Vehicle Vision Processing: A View from the Edge,” a Presentation from NXP Semiconductors

Algorithms, Automotive, Edge AI and Vision Alliance, NXP Semiconductors, Processors, Sensors and Cameras, Software, Summit 2018, Tools, Videos /

Ali Osman Ors, Director of Automotive Microcontrollers and Processors at NXP Semiconductors, presents the “Role of the Cloud in Autonomous Vehicle Vision Processing: A View from the Edge” tutorial at the May 2018 Embedded Vision Summit. Regardless of the processing topology—distributed, centralized or hybrid —sensor processing in automotive is an edge compute problem. However, with

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Computer Vision for Augmented Reality in Embedded Designs

Algorithms, Articles, Augmented Reality, Edge AI and Vision Alliance, NXP Semiconductors, Processors, Sensors and Cameras, Software, Synopsys, Technical Articles, Tools, videantis /

Augmented reality (AR) and related technologies and products are becoming increasingly popular and prevalent, led by their adoption in smartphones, tablets and other mobile computing and communications devices. While developers of more deeply embedded platforms are also motivated to incorporate AR capabilities in their products, the comparative scarcity of processing, memory, storage, and networking resources

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OpenVX Implementations Deliver Robust Computer Vision Applications

Algorithms, Articles, Cadence, Edge AI and Vision Alliance, Intel, NXP Semiconductors, Processors, Software, Technical Articles, Tools, VeriSilicon /

Key to the widespread adoption of embedded vision is the ease of developing software that runs efficiently on a diversity of hardware platforms, with high performance, low power consumption and cost-effective system resource needs. In the past, this combination of objectives has been a tall order, since it has historically required significant code optimization for

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OpenVX Enhancements, Optimization Opportunities Expand Vision Software Development Capabilities

Algorithms, Articles, Cadence, Edge AI and Vision Alliance, Intel, NXP Semiconductors, Processors, Software, Technical Articles, Tools, VeriSilicon /

Key to the widespread adoption of embedded vision is the ease of developing software that runs efficiently on a diversity of hardware platforms, with high performance, low power consumption and cost-effective system resource needs. In the past, this combination of objectives has been a tall order, since it has historically required significant code optimization for

OpenVX Enhancements, Optimization Opportunities Expand Vision Software Development Capabilities Read More +

“Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles,” a Presentation from NXP Semiconductors

Algorithms, Automotive, Edge AI and Vision Alliance, NXP Semiconductors, Object Identification, Object Tracking, Optical Character Recognition, Processors, Sensors and Cameras, Software, Tools, Videos /

Ali Osman Ors, Director of Automotive Microcontrollers and Processors at NXP Semiconductors, presents the "Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles" tutorial at the May 2017 Embedded Vision Summit. A diverse set of sensor technologies is available and emerging to provide vehicle autonomy or driver assistance. These sensor technologies often

“Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles,” a Presentation from NXP Semiconductors Read More +

“Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles,” a Presentation from NXP Semiconductors

Algorithms, Automotive, Edge AI and Vision Alliance, NXP Semiconductors, Object Identification, Object Tracking, Optical Character Recognition, Processors, Sensors and Cameras, Software, Tools, Videos /

Ali Osman Ors, Director of Automotive Microcontrollers and Processors at NXP Semiconductors, presents the "Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles" tutorial at the May 2017 Embedded Vision Summit. A diverse set of sensor technologies is available and emerging to provide vehicle autonomy or driver assistance. These sensor technologies often

“Choosing the Optimum Mix of Sensors for Driver Assistance and Autonomous Vehicles,” a Presentation from NXP Semiconductors Read More +

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

Algorithms, 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

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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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PO Box #4446
Walnut Creek, CA 94596

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Phone: +1 (925) 954-1411
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