Vision Components has developed new 3D laser scanners with powerful integrated electronics. The VCnano3D-Z-series embedded vision systems are compact, lightweight, and easy-to-integrate in OEM applications. They contain a Xilinx Zynq SoC, which comprises a dual-core ARM processor and an FPGA. In order to determine line coordinates in laser triangulation, a point cloud has to be […]
Embedded 3D Image Processing Read More +
NVIDIA RTX Hybrid Graphics Made Possible by AI and Ray Tracing Inventions; Delivers 6x Performance Boost; September Availability Monday, August 20, 2018—Gamescom—NVIDIA today unveiled the GeForce RTX™ series, the first gaming GPUs based on the new NVIDIA Turing™ architecture and the NVIDIA RTX™ platform, which fuses next-generation shaders with real-time ray tracing and all-new AI
10 Years in the Making: NVIDIA Brings Real-Time Ray Tracing to Gamers with GeForce RTX Read More +
VISION PROCESSING IN THE CLOUD Introduction to Creating a Vision Solution in the Cloud A growing number of applications utilize cloud computing for execution of computer vision algorithms. In this presentation, Nishita Sant, Computer Vision Scientist at GumGum, introduces the basics of creating a cloud-based vision service, based on GumGum's experience developing and deploying a
Embedded Vision Insights: August 21, 2018 Edition Read More +
Markus Tremmel, Chief Expert for ADAS at Bosch, presents the “Computer Vision Hardware Acceleration for Driver Assistance” tutorial at the May 2018 Embedded Vision Summit. With highly automated and fully automated driver assistance system just around the corner, next generation ADAS sensors and central ECUs will have much higher safety and functional requirements to cope
“Computer Vision Hardware Acceleration for Driver Assistance,” a Presentation from Bosch Read More +
This blog post was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. Self-driving cars and trucks are the talk of the town, but trains could be first out of the station as a fully autonomous form of transportation. That’s because — unlike passenger vehicles or long-haul trucks — a
AI Think I Can: Why GPUs Could Be the Engine Leading Us to Autonomous Trains Read More +
This market research report was originally published at Tractica's website. It is reprinted here with the permission of Tractica. GPUs and CPUs Lead the Market Today, But There Is an Expanding Role for FPGAs, ASICs, SoC Accelerators, and Other Emerging Chipsets Artificial intelligence (AI) technology is progressing at a rapid pace, as is the application
Deep Learning Chipset Market to Reach $66.3 Billion by 2025 Read More +
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
Computer Vision for Augmented Reality in Embedded Designs Read More +
Mario Munich, Senior Vice President of Technology at iRobot, presents the “Roomba 980: Computer Vision Meets Consumer Robotics” tutorial at the May 2018 Embedded Vision Summit. In 2015, iRobot launched the Roomba 980, introducing intelligent visual navigation to its successful line of vacuum cleaning robots. The availability of affordable electro-mechanical components, powerful embedded microprocessors and
“The Roomba 980: Computer Vision Meets Consumer Robotics,” a Presentation from iRobot Read More +
This market research report was originally published at Tractica's website. It is reprinted here with the permission of Tractica. Investment in AI for Autonomous Vehicles Will Rise Rapidly Over the Next Few Years, in Addition to Applications Focused on Personalization, Predictive Maintenance, Localization and Mapping, and Other Automotive Use Cases The automotive industry is among
László Kishonti, founder and CEO of AImotive, presents the “How Simulation Accelerates Development of Self-Driving Technology” tutorial at the May 2018 Embedded Vision Summit. Virtual testing, as discussed by Kishonti in this presentation, is the only solution that scales to address the billions of miles of testing required to make autonomous vehicles robust. However, integrating
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