StradVision Wins AutoSens 2022 Gold Award for Perception Software

  • This is the second year in a row where StradVision’s SVNet deep-learning based camera perception software has been honored as a top prize winner of the industry

SEOUL, South Korea, Sept. 19, 2022 /PRNewswire/ — StradVision, an AI-based video perception  technology company for Autonomous Vehicles and ADAS, is honored to announce that its SVNet software was once again selected as the ‘Best-in-Class Software for Perception Systems’ during the 2022 AutoSens Awards in Brussels, Belgium.

StradVision Wins AutoSens 2022 Gold Award for Perception Software
StradVision Wins AutoSens 2022 Gold Award for Perception Software

The AutoSens Awards have become one of the industry’s leading events for the ADAS and autonomous vehicle technology community, recognizing the most innovative companies and products leading the global autonomous driving industry. StradVision’s Gold Award selection was made during this year’s award ceremony held on September 13. The company’s SVNet was recognized for the second year in a row regarding its deep learning-based camera perception software that continues to mature within the automotive space and accelerate the ADAS and autonomous driving sector forward. StradVision’s Dean Kim (Vice President of Business Development) and Andreas vom Felde (General Manager & Head of Sales Region Europe) were in event attendance to accept the award.

"This high recognition by AutoSens for the second year is a tremendous honor for our company," said Junhwan Kim, CEO of StradVision. "Our goals have been very ambitious for business growth and innovation, and this year has brought many milestone moments for us. AutoSens’ Gold Award for our SVNet perception software will continue our motivation as we pursue more ways to advance autonomous driving and ADAS solutions for the global community."

"We’ve experienced exponential business growth and recognition from the global community over the past year," said Dean Kim, StradVision’s Vice President of Business Development. "Seeing our SVNet software selected once again by AutoSens this year is incredible and we believe further spotlights the potential our perception solutions can bring for OEMs and Tier-1s in the automotive industry worldwide."

StradVision’s SVNet is state-of-the-art software that powers the perception technology behind ADAS and autonomous vehicles, enabling external vehicle perception via 14+ platforms across Qualcomm, Texas Instruments, Renesas, NVIDIA and other chipset makers to accurately and safely detect and recognize objects (even in poor lighting or harsh weather conditions), such as other vehicles, lanes, pedestrians, animals, free space, traffic signs, and lights.  SVNet was the first network to run deep learning-based object detection software on TDA2x, R-car V3H, V3M, and H3, and now also provides deep neural network across Snapdragon Ride, Orin, Jacinto, R-car series and Ambarella CV series. Other StradVision products include SVNet Tools, which removes the need to have a large team spending hundreds of hours correcting objects with the risk of human error.

About StradVision

Founded in 2014, StradVision is an automotive industry pioneer in AI-based vision processing technology for Advanced Driver Assistance Systems (ADAS). The company is accelerating the advent of fully autonomous vehicles by making ADAS features available at a fraction of the market cost compared with competitors. StradVision’s SVNet is being deployed on various vehicle models in partnership with OEMs and powers ADAS & Autonomous Vehicles worldwide and is serviced by over 300 employees in Seoul, San Jose, Detroit, Tokyo, Shanghai, Friedrichshafen, and Dusseldorf. StradVision has been honored with the Gold Award at the 2021 and 2022 AutoSens Awards for Best-in-Class Software for Perception Systems, and the 2020 Autonomous Vehicle Technology ACES Award in Autonomy (Software Category). In addition, StradVision’s software is certified to the ISO 9001:2015 for Quality Management System and ISO 26262 for Automotive Functional Safety.

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