Korean startup StradVision Inc. recently announced that it had raised $27 million in Series B funding. The Seoul based company makes vision processing technology for autonomous vehicles and advanced driver assistance systems, or ADAS.
The funding round was led by Posco Capital. It included investment from IDG Capital, Industrial Bank of Korea, Lighthouse Combined Investment, LSS Private Equity, Mirae Asset Venture Investment, Neoplux, and Timefolio Asset Management. With this fresh funding, StradVision has raised a total of $40 million to date.
The company had got its Series A investment of 2.5 billion won or approximately $ 2.2 million from the Japanese VC Global Brain in 2018. The company was founded in 2014 and is based in San Jose, California, with an office in Pohang, South Korea.
In a statement to media, the CEO of the company, Junhwan Kim, said, “StradVision’s software solutions for autonomous vehicles and ADAS are proving successful and attractive to leading automakers and suppliers, as our latest round of funding strongly confirms. We appreciate all of our new investors coming on board, and StradVision will use this funding to take our groundbreaking products to the next level as we lead the advancement of camera technology in autonomous vehicles.”
Deep Learning-Based Camera Detection Technology
StradVision has developed a deep learning-based camera image detection technology for the automotive industry that plays a critical role in ADAS capabilities such as Automatic Emergency Braking and Blindspot Detection. StradVision’s technology is 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. The company has 75 registered patents relating and 79 more applications are in process.
StradVision’s SVNet software — which includes SVNet External, SVNet Internal and SVNet Tools 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.
SVNet’s Auto Labeling System (ALS) produces training data with minimal human input, and a semi-supervised learning-based SVNet training tool enables customers to enhance SVNet by themselves during mass production projects. This application of unsupervised learning, which functions similar to how the human brain organizes data, gives machines nearly limitless understanding of the visual information they see.
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 — including trucks, self-driving buses and passenger vehicles.
Global partnerships and ambitious plans
StradVision has multiple mass production projects ongoing in China and Europe, in partnership with leading global OEMs and Tier 1 suppliers. The company’s vision is to have millions of vehicles on the roadways using its software for Autonomous Vehicles and ADAS systems by 2021 — including SUVs, sedans and buses. StradVision recently earned the coveted Automotive SPICE CL2 certification, as well as China’s Guobiao (GB) certificate — and StradVision is already deploying ADAS vehicles on China’s roads.
StradVision, which currently has more than 105 employees in the United States, Germany, Korea, and Japan, recently partnered with a leading global Tier 1 supplier in cooperation and a number of commercial vehicle manufacturers on a side-camera project, and custom camera technology for autonomous buses. Current StradVision projects range from Autonomy Levels 2 through 4.
