Syntiant’s Deep Learning Computer Vision Models Deployed on Renesas RZ/V2L Microprocessor
Designed for edge devices and optimized to reduce latency and memory footprint, Syntiant’s hardware-agnostic deep learning models can be used for multiple vision-based applications such as object detection, face recognition, pose estimation, background subtraction and image classification.
- Designed for edge devices and optimized to reduce latency and memory footprint, Syntiant’s hardware-agnostic deep learning models can be used for multiple vision-based applications such as object detection, face recognition, pose estimation, background subtraction and image classification.
- “Our ongoing collaboration with the team at Syntiant now includes integrating their computer vision models into our DRP-AI accelerator core for enhanced AI vision processing,” said Shigeki Kato, vice president of the Enterprise Infrastructure Business Division at Renesas.
- Models are further optimized to verify performance and reliability for high performance across numerous industries, ranging from smart home to retail analytics.
- Demonstrations of the Syntiant and Renesas RZ/V2L combined solution will occur May 22-24 at the Renesas booth (#403) during the 2023 Embedded Vision Summit at the Santa Clara Convention Center.