StradVision provides 6 key features of SVNet to D3 Engineering’s virtual Demonstrator of Autonomous Vehicle Equipment platform
StradVision, a leading innovator in AI-based camera perception software for Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV), today announced its collaboration with D3 Engineering on an Automotive Front Camera solution delivering market-leading performance and price efficiency.
The solution integrates a D3 DesignCore® platform for product development with StradVision’s deep learning based front camera software ‘SVNet’. In this collaboration, StradVision provides 6 key perception features of SVNet including Lane Detection, Traffic Sign Detection, Traffic Light Detection, Vehicle Detection, Pedestrian Detection, and Free Space Detection to this virtual demo platform.
The solution can be viewed at CES 2021 on D3 Engineering’s virtual D.A.V.E. (Demonstrator of Autonomous Vehicle Equipment) platform. Visitors to the virtual platform can experience a guided virtual ride from on-call D3 team members during CES exhibitor showcase hours.
“We are delighted to have a great opportunity to showcase the future of autonomous driving technology with our industry leading partner, at CES 2021. SVNet is one of the most efficient vision processing solutions offers groundbreaking AI-based recognition performance with less consumption of computing power, and we believe our solution will accelerate autonomous driving vehicle comes to our daily lives,” said Junhwan Kim, CEO of StradVision.
“We are excited to continue working together with StradVision to offer market-leading Automotive Front Camera solutions on our DesignCore platform,” said Jerome Barczykowski, Business Development Operations Manager at D3 Engineering. “The DesignCore platform incorporates proven collections of hardware, software, applications, and testing. Combined with StradVision algorithms, the solution accelerates time-to-market while reducing the cost and risk of production product development.”
StradVision is accelerating the advancement of autonomous vehicles through SVNet, an AI-based object recognition software. Compared to competitors, SVNet achieves much higher efficiency in memory usage and energy consumption, and can be customized and optimized to any system on a chip (SoC), thanks to its patented and cutting-edge Deep Neural Network. The software also works seamlessly with other sensors such as LiDAR and RADAR to achieve surround vision.
SVNet is currently used in mass production models of ADAS and autonomous driving vehicles that support safety function Levels 2 to 4, and will be deployed in more than 8.8 million vehicles worldwide.