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Computational sensing and embedded low-power processing

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Computational sensing is where optics, sensing, and processing are combined to maximize the collection of information for a given application. Computational sensing systems provide real-time information capture of multi-modality sensors, special purpose optical paths and processing to extract signal information.  

CVT has developed several computational sensing technologies and systems for government and commercial clients.   

SmartVision

CVT developed SmartVision technology to improve a sensor’s ability to collect the most salient information in a large, cluttered scene and share this data with end-users over narrow-bandwidth data links. SmartVision dynamically optimizes single or multi-modality sensing parameters (e.g., integration time, frame rate, wavelength) in local regions of interest across the scene to gather the best mission information. 

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Multi-sensor fusion and visualization 

CVT has also developed very low-power and small-sized sensing systems that combine multi-modal, multi-aperture and multi-exposure sensor information into a single display or video feed. Real-time, very low-latency fusion and alignment of wearable or flown sensors are presented to users or machine processing to respond rapidly to changing information. Through computer vision and optimized small-footprint machine learning-based algorithms, the presentation of information to the user in a single display greatly reduces their workload. 

Embedded low-power processing

Model airplane with adult and kid (text: SRI's low power processors integrated in todays' robotic platforms)

CVT has vast experience in developing low-power AI edge processing solutions for a range of platforms and applications.  On DARPA Hyper-Dimensional Data Enabled Neural Networks (HyDDENN), CVT demonstrated non- Multiply Accumulate (MAC) quantized neural networks with 100X reduction in power-latency factor, performing real-time neural network reconfiguration, using a variety of commercial off the shelf (COTS) field programmable gate arrays (FPGAs).  Building on HyDDENN, CVT is now developing our NeuroEdge technology to implement low-power edge computing on COTS graphics processing unit (GPU) FPGA and AI-Processors using our newly developed NeuroEdge Software Development Kit (SDK). For Advanced Research Projects Agency – Energy (ARPA-E) we developed a battery powered, multi-year operational occupancy sensor systems for household and commercial buildings to reduce building HVAC power consumption. 

Recent work

  • BASF selects SRI International to help refine and improve computer vision applications
    November 22, 2021

    BASF selects SRI International to help refine and improve computer vision applications

    BASF, the world’s largest chemical producer, identified Computer Vision as a critical technology for addressing a significant number of its global and societal challenges.

  • SRI International’s Driver Monitoring System selected as winner of AutoTech Breakthroughs’s Auto Sensor Innovation of the Year award
    December 7, 2020

    SRI International’s Driver Monitoring System selected as winner of AutoTech Breakthroughs’s Auto Sensor Innovation of the Year award

    SRI International is proud to announce that the Center for Vision Technologies Lab has been awarded the Auto Sensor Innovation of the Year award for our Driver Monitoring System from AutoTech Breakthrough. AutoTech Breakthrough is part of the Tech Breakthrough Awards program, a premier awards and recognition platform founded to recognize artificial intelligence related technology innovators, […]

  • SRI International Partners with Kawada Technologies and Kawada Industries to Introduce Weld-Visualization Technology and Next-Generation, 3D-Welding Helmet
    September 11, 2019

    SRI International Partners with Kawada Technologies and Kawada Industries to Introduce Weld-Visualization Technology and Next-Generation, 3D-Welding Helmet

    MENLO PARK, CA. September 11, 2019 – SRI International (SRI), a nonprofit research center, announced their collaboration with Kawada Technologies, Inc. (KTI) and Kawada Industries to develop Xtreme Dynamic Range (XDR) weld visualization technology that uses image processing to visualize live weld details to the welder safely. XDR has been further applied to a next-generation, 3D-welding helmet that uses cameras […]

Recent publications

more +
  • October 14, 2022

    Low-Power In-Pixel Computing with Current-Modulated Switched Capacitors

    SRI authors: David Zhang, Gooitzen van der Wal, Michael A. Isnardi, Michael Piacentino
  • August 25, 2022

    Sensor Trajectory Estimation by Triangulating Lidar Returns

    SRI authors: Charles Karney
  • August 17, 2022

    Learning with Local Gradients at the Edge

    SRI authors: David Zhang, Michael Piacentino

Featured reports and publications

Mar. 29 – Apr. 1, 2021

Hyper-Dimensional Analytics of Video Action at the Tactical Edge

SRI authors: D. Zhang, M. Piacentino

Dec 10-16, 2019

Bit Efficient Quantization for Deep Neural Networks

SRI authors: D. Zhang, and S. Chai

November 12, 2018

Generalized Ternary Connect: End-to-End Learning and Compression of Multiplication-Free Deep Neural Networks

SRI author: Sek Chai

November 16, 2018

BitNet: Bit-Regularized Deep Neural Networks

SRI author: Sek Chai

March 24, 2017

Low Precision Neural Networks using Subband Decomposition

SRI author: David Zhang

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