SAN JOSE, Calif., Sept. 5, 2019 /PRNewswire/ -- StradVision is on-site at AutoCam 2019 from Sept. 5-6, demonstrating their SVNet software, a central component in five production projects in Germany and China.
StradVision is demonstrating its SVNet External and SVNet Internal products in partnership with various chipsets — including Texas Instruments' TDA2, Renesas V3H, and NVIDIA's Xavier chipsets.
AutoCam is the world's preeminent conference focused on perception technology in ADAS and autonomous driving. Representatives from OEMs around the world are seeking the latest technology to advance their autonomous programs.
"We are excited to attend this prestigious event and show key automotive industry stakeholders the benefits of our SVNet software," said StradVision CEO Junhwan Kim. "Our deep-learning ability and compatibility records set StradVision apart in the field of vision processing for the autonomous landscape."
The event brings together leading engineers in the automotive field as they plan and implement growth strategies. Key topics include the importance of adaptability to harsh environments, and adhering to privacy regulations.
StradVision — which recently earned the coveted ASPICE CL2 certification, as well as China's Guobiao (GB) certificate — continues to expand its production in China, and is already deploying ADAS vehicles on Chinese roads.
Kim added, "Chinese OEMs and Tier 1s are an important part of the path forward for StradVision, and the recent certifications show the level of success possible when SVNet software is used on autonomous production projects."
StradVision's SVNet software provides real-time feedback, detects obstacles in blind spots, and alerts drivers to potential accidents. SVNet also prevents collisions by detecting lanes, abrupt lane changes and vehicle speeds, even in poor lighting and weather conditions. StradVision works with automotive OEMs and Tier 1 suppliers to enable functions such as automatic emergency braking and blind-spot detection.
StradVision is an industry pioneer in vision processing technology, providing the underpinning that will allow ADAS in autonomous vehicles to reach the next level of safety, and helping to usher in the era of the fully autonomous vehicle.