This blog post was originally published by AImotive. It is reprinted here with the permission of AImotive. The unprecedented situation that has developed as a result of the current COVID-19 outbreak has brought a new range of challenges to the fore in automotive software development. At AImotive, we are relying on our highly automated development […]
Accelerating Remote Automotive Development Read More +
Outlines: Automotive lighting market is expected to reach US$38.8 billion by 2024, with 4,9% CAGR between 2018 and 2024. Evolution of lighting technologies enables new functionalities. ADAS vehicles: sensors integration is becoming mandatory. LiDAR integration: OEM s have several requirements at different levels. “Autonomous vehicle technologies have a direct impact on traditional vehicles market and
Automotive Lighting: From “Vision” to “Driving Assistance” Read More +
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.
Speeding Up Deep Learning Inference Using TensorFlow, ONNX, and TensorRT Read More +
John Lorenz, Market and Technology Analyst for Computing and Software at Yole Développement, delivers the presentation “Market Analysis on SoCs for Imaging, Vision and Deep Learning in Automotive and Mobile Markets” at the Edge AI and Vision Alliance’s March 2020 Vision Industry and Technology Forum. Lorenz presents Yole Développement’s latest analysis on the evolution of
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Deep neural network takes a two-stage approach to address lidar processing challenges. Editor’s note: This is the latest post in our NVIDIA DRIVE Labs series, which takes an engineering-focused look at individual autonomous vehicle challenges and how
Laser Focused: How Multi-View LidarNet Presents Rich Perspective for Self-Driving Cars Read More +
What’s New: The Institute of Electrical and Electronics Engineers (IEEE) has approved a proposal to develop a standard for safety considerations in automated vehicle (AV) decision-making and named Intel Senior Principal Engineer Jack Weast to lead the workgroup. Participation in the workgroup is open to companies across the AV industry, and Weast hopes for broad
IEEE to Define a Formal Model for Safe Automated Vehicle Decision-Making Read More +
Phil Magney, founder of VSI Labs, presents the “Improving the Safety and Performance of Automated Vehicles Through Precision Localization” tutorial at the May 2019 Embedded Vision Summit. How does a self-driving car know where it is? Magney explains how autonomous vehicles localize themselves against their surroundings through the use of a variety of sensors along
Gergely Debreczeni, Chief Scientist at AImotive, presents the “Distance Estimation Solutions for ADAS and Automated Driving” tutorial at the May 2019 Embedded Vision Summit. Distance estimation is at the heart of automotive driver assistance systems (ADAS) and automated driving (AD). Simply stated, safe operation of vehicles requires robust distance estimation. Many different types of sensors
Andrew Richards, CEO and Co-founder of Codeplay Software, presents the “Can We Have Both Safety and Performance in AI for Autonomous Vehicles?” tutorial at the May 2019 Embedded Vision Summit. The need for ensuring safety in AI subsystems within autonomous vehicles is obvious. How to achieve it is not. Standard safety engineering tools are designed
Tom Wilson, Vice President of Automotive at Graphcore, presents the “DNN Challenges and Approaches for L4/L5 Autonomous Vehicles” tutorial at the May 2019 Embedded Vision Summit. The industry has made great strides in development of L4/L5 autonomous vehicles, but what’s available today falls far short of expectations set as recently as two to three years
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.
Berkeley Design Technology, Inc.
PO Box #4446
Walnut Creek, CA 94596
