stradvision

Event scheduled for February 25th helps encourage cooperation between innovative startups and corporate partners

StradVision, an innovator in vision processing technology for Autonomous Vehicles, has announced it was among an elite group invited to present its technology to automotive industry leaders at Startup Autobahn Selection Day. The event will take place in ARENA2036 in Stuttgart, Germany, on February 25^th, 2020.

StradVision's CEO, Junhwan Kim, will present an elevator pitch in front of the leaders of the German automotive industry. Kim will highlight StradVision's progress in the field of deep-learning based vision perception technology, and explain how SVNet will benefit the German automakers.

"StradVision looks forward to the opportunity to show German automakers the benefits of our innovative software to their development of ADAS systems and Autonomous Vehicles," Kim said. "With our deep-learning approach, new technologies are being developed by StradVision at a rapid pace to ensure the effectiveness of these advanced safety systems."

An industry leader in camera perception software, StradVision plays a critical role in ADAS capabilities such as Automatic Emergency Braking and Blind-Spot Detection. StradVision's technologies are based on its SVNet Deep Learning-based software, which enables high-level perception abilities including: Lane Detection, Traffic Light & Sign Detection/Recognition, Object Detection and Free Space Detection.

At the Startup Autobahn event, in addition to its presentation, StradVision will have a booth where they will display their latest technologies, including:

StradVision's technology plays a critical role in multiple mass production projects ongoing around the world from level 2 to 4 autonomy. StradVision has also earned the coveted Automotive SPICE CL2 certification, as well as China's Guobiao (GB) certificate — and is already deploying ADAS vehicles on Chinese roads.

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.

When paired with commercial automotive-grade Systems on Chip (SoCs), SVNet's AI-based Deep Neural Network is fully optimized and interacts in real-time with the world it is viewing. Offering minimum latency and power consumption, it allows for proper real-world detection, tracking, segmentation and classification, and will be implemented in multiple production projects throughout 2020.

Source : https://prn.to/3bVnD71