SEOUL — STRADVISION, an automotive industry pioneer in deep learning-based vision perception technology, has been selected as a Renesas’ R-Car Consortium Proactive Partner Program member for five consecutive years.
The R-Car Consortium, established by Renesas, serves as an inclusive platform that unites system integrators, middleware/application developers, operating systems, and tool vendors. This collaborative space empowers customers to access tailored solutions for their specific needs. Within this framework, partners offer expertise to develop cutting-edge connected cars and ADAS solutions jointly.
Meeting the consortium’s benchmarks of “open,” “innovative,” and “trusted,” STRADVISION successfully earned recognition as a 2023 Proactive Partner, backed by a strong track record in the automotive sector. This achievement facilitates swift customer engagement, exemplifying their commitment to excellence.
Through this initiative, STRADVISION will enhance its expertise through a range of activities encompassing promotion, technical support, education, and more. These endeavors are aimed at precisely aligning with customer needs and demands.
“Attaining membership in the Renesas R-Car Consortium Proactive Partner Program for five successive years is truly an honor,” stated STRADVISION’s COO and US CEO, Sunny Lee. “Seizing this moment, we intend to forge fresh business connections within the automotive sector, thereby making meaningful contributions to the advancement of ADAS technology.”
Since the joint announcement of collaboration in September 2019, STRADVISION has maintained a close partnership with Renesas. Their collaboration is centered around the development of a deep learning-based object recognition solution tailored for smart cameras utilized in ADAS (advanced driver-assistance systems) applications.
STRADVISION’s SVNet is an ultra-light, high-efficiency solution that implements deep learning-based object recognition with minimal computation and power consumption. It supports over 18 System-on-Chips (SoCs) platforms and provides over 30 object recognition functions.
It actively participates in multiple projects for mass-producing vehicle models with autonomous driving level 2 or higher, leveraging solid technology and flexibility gained from mass production in the automobile industry.
