Syntiant Corp., a leader in edge AI deployment, has deployed its off-the-shelf deep learning computer vision (CV) models on integrated DRP-AI (dramatic reconfigurable processor) cores on Renesas RZ/V2L microprocessors (MPUs). announced that it is ready to be installed. ) will allow developers to quickly add intelligence to camera-based devices without incurring energy overhead.
Syntiant’s hardware-agnostic deep learning models are designed for edge devices and optimized to reduce latency and memory footprint for object detection, face recognition, pose estimation, background subtraction, image classification, and more. can be used for multiple vision-based applications. Using Syntiant’s inference software development kit (SDK), the company’s CV algorithms are integrated into a variety of hardware platforms, supporting both traditional and modern computing architectures, as well as embedded Reduce costs and speed time to market by solving critical problems directly on the device. .
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“By working to introduce a solution that integrates our computationally efficient vision model into the Renesas RZ/V2L MPU, we will be able to develop next-generation embedded vision for cameras used in homes, smart cities, retail POS systems, autonomous robots, and more. It enables applications,” use cases,” said Mallik Moturi, chief business officer at Syntiant. “By combining our technologies, developers can quickly and easily create intelligent, energy-efficient devices that can operate in a wide range of environments.”
Renesas RZ/V2L MPU with Cortex-A55 (1.2GHz) CPU and built-in DRP-AI accelerator, providing both real-time AI inference and image processing for camera support such as color correction and noise reduction To do. The platform also features a 16-bit DDR3L/DDR4 interface and a built-in 3D graphics engine with Arm Mali-G31 and video codec (H.264). Integrating Syntiant’s solution into the DRP-AI core supports parallel execution of up to five different vision-based classes, providing superior functionality and efficiency.
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Shigeki Kato, vice president of Renesas’ Enterprise Infrastructure Division, said: “Our ongoing collaboration with Syntiant’s team includes integrating their computer vision models into our DRP-AI accelerator cores to enhance AI vision processing.” provides both high performance and low power consumption, and can reduce processing time by pre-processing images and offloading the CPU, which is useful for applications such as barcode scanning and iris detection and extraction. ideal for complex image processing.”
Syntiant’s CV model dynamically scales according to input complexity due to its unique adaptive neural network structure. The model is further optimized to validate high-performance performance and reliability across a variety of industries, from smart home to retail analytics.
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