“The collaboration [with Algolux] will enable [Renesas'] R-Car customers to effectively leverage their resources while optimizing system performance, and accelerate time to market.” - Naoki Yoshida, Vice President of Automotive Digital Products Marketing Division at Renesas
MONTREAL (PRWEB) April 06, 2021
Algolux, the leading provider of robust and scalable perception solutions, has announced its collaboration with Renesas, a premier supplier of advanced semiconductor solutions, to enable vision system design teams to automatically optimize cameras based on R-Car system-on-chips (SoCs) at scale with the new cloud-enabled Atlas Camera Optimization Suite.
Atlas automates today’s months-long manual ISP tuning process to maximize computer vision accuracy and image quality in only days, an improvement of up to 100x in scalability and resource leverage. The workflow permits rapid evaluation of different camera sensors and lenses for cost reduction, best performance, or to adapt to changes in customer requirements. For teams developing computer vision applications, Atlas can determine the optimal ISP parameter set to for highest accuracy, which is not possible with today’s manual ISP tuning approaches.
The cloud-enabled workflow supports ISPs embedded in Renesas R-Car SoCs, such as the R-Car V3H and R-Car V3M for intelligent and automated driving (AD) vehicles, and the recently announced R-Car V3U ASIL D SoC for advanced driver assistance systems (ADAS) and AD systems.
In a recently published case study with a leading automotive Tier 1, Atlas was applied to their vision system based on the Sony IMX490 HDR sensor and the Renesas R-Car V3H ISP. Object detection accuracy was improved by up to 48 mAP points vs. the manual image quality tuned baseline across well-illuminated to very dark scenarios. You can download the case study and watch a product demonstration of the cloud-based workflow.
“As an industry-recognized leader in robust and scalable perception solutions, Algolux continues to democratize automated camera optimization, reducing the manual ISP tuning burden for developers. The collaboration will enable our R-Car customers to effectively leverage their resources while optimizing system performance, and accelerate time to market,” said Naoki Yoshida, Vice President of Automotive Digital Products Marketing Division at Renesas.
“Thanks to our close collaboration with Renesas, Algolux is in a unique position to help automotive ADAS and autonomous vehicle vision systems teams using R-Car SoCs. Atlas uses machine learning to significantly improve image quality and computer vision accuracy, while addressing painful resource and schedule risks with industry-leading scalability,” said Allan Benchetrit, CEO of Algolux.
Algolux is an award-winning AI software company delivering the industry’s most robust and scalable perception for all conditions, addressing both existing cameras and new designs through cloud-based tools and embedded software. The company was founded on groundbreaking research at the intersection of deep learning, computer vision, and computational imaging. Our computer vision and image optimization solutions address the mission-critical issue of safety for automotive ADAS, autonomous vehicles, fleets, autonomous mobile robots, and video security.
Algolux is headquartered in Montreal, with offices in Palo Alto and Munich, and has over 50 employees (85% in R&D). The company has numerous engagements spanning automotive, AVs, fleet management, and video security with leading customers worldwide.
Learn more at algolux.com
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