Algolux wins Vision Product of the Year Award for Best Automotive Solution
“We congratulate Algolux on the recognition of its CANA DNN software for robust computer vision perception as Vision Product of the Year Awards, Best Automotive Solution.” - Jeff Bier, founder of the Embedded Vision Alliance
SANTA CLARA, Calif. (PRWEB) May 22, 2018
Algolux, the leading provider of machine learning optimization platforms for autonomous vision, has won the Vision Product of the Year Award at the Embedded Vision Summit. Algolux was presented with the award for Best Automotive Solution for its CANA full-stack deep neural network (DNN) for robust perception as determined by an independent panel of computer vision expert judges.
Open to all Embedded Vision Alliance® Member companies, the Vision Product of the Year Award winning entries are selected by an independent panel of judges based on innovation, impact on customers and the market, and competitive differentiation.
Perception accuracy for autonomous vision in challenging imaging conditions, such as low light and adverse weather, is mission-critical for safety in ADAS and autonomous driving. CANA applies a novel end-to-end DNN that integrates the image formation model with the high-level computer vision model to significantly improve accuracy versus today’s alternative state of the art approaches.
“We are honored to win this Vision Product of the Year Award for automotive. This acknowledgment from computer vision industry experts provides distinct recognition that we are uniquely addressing critical challenges,” said Allan Benchetrit, Algolux President and CEO. “The award highlights how Algolux’s autonomous vision technology is on its way to making a meaningful impact on the mission-critical concern of safety in the development and deployment of vision systems in the automotive industry.”
"The Vision Product of the Year Awards recognize the most innovative products and technologies addressing the industry’s hardest challenges in computer vision,” said Jeff Bier, founder of the Embedded Vision Alliance. “We congratulate Algolux on the recognition of its CANA DNN software for robust computer vision perception as Best Automotive Solution.”
About Algolux
Algolux enables autonomous vision – empowering cameras to see more clearly and perceive what cannot be sensed with today’s imaging and vision systems. Computer vision is at the heart of autonomous cars, ADAS, mobile devices, security cameras (IoT), AR/VR, robotics, drones, and medical equipment, leading the next wave of market growth and social impact. Developed by an industry-recognized team of machine learning, computer vision, and image processing researchers, our patented machine-learning technologies address the complexity of optimizing imaging and vision systems while improving the costs, time-to-market, and expertise challenges faced by product development teams.
Visit us at http://www.algolux.com.
About The Embedded Vision Alliance
The Embedded Vision Alliance is a worldwide industry partnership bringing together technology providers and end-product companies who are enabling innovative and practical applications for computer vision for a range of market segments and applications, including automotive, consumer electronics, gaming, imaging, and more. Membership is open to any company that supplies or uses technology for computer vision systems and applications. For more information on the Alliance, visit https://www.embedded-vision.com.
About The Vision Product of the Year Awards Program
The Vision Product of the Year Awards are open to all Embedded Vision Alliance® Member companies and celebrate the innovation of the industry’s leading companies that are enabling the next generation of computer vision applications. Winning entries are selected by an independent panel of judges based on innovation, impact on customers and the market, and competitive differentiation.
© Copyright 2018 Algolux, Inc. Algolux, the Algolux logo, CRISP, CRISP-ML, CANA, and other designated brands included herein are trademarks of Algolux in the United States and other countries. All other trademarks are the property of their respective owners.