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公开(公告)号：US11348033B2
公开(公告)日：2022-05-31
申请号：US16318667
申请日：2017-07-21
Applicant: SRI International
Abstract: A system comprises one or more observation stations. Each observation station of the one or more observation stations comprises a corresponding set of one or more sensors. Additionally, the system comprises one or more physical machines that implement a computation engine configured to receive first observation data from the one or more observation stations. The computation engine may use the first observation data to train a machine learning system. The computation engine may subsequently use the trained machine learning system to provide feedback regarding an additional instance of the observation subject. The computation engine outputs the feedback.
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12.发明授权公开(公告)号：US11328206B2
公开(公告)日：2022-05-10
申请号：US15625578
申请日：2017-06-16
Applicant: SRI International
Inventor： Sek M. Chai , David C. Zhang , Mohamed R. Amer , Timothy J. Shields , Aswin Nadamuni Raghavan , Bhaskar Ramamurthy
Abstract: Operations of computing devices are managed using one or more deep neural networks (DNNs), which may receive, as DNN inputs, data from sensors, instructions executed by processors, and/or outputs of other DNNs. One or more DNNs, which may be generative, can be applied to the DNN inputs to generate DNN outputs based on relationships between DNN inputs. The DNNs may include DNN parameters learned using one or more computing workloads. The DNN outputs may be, for example, control signals for managing operations of computing devices, predictions for use in generating control signals, warnings indicating an acceptable state is predicted, and/or inputs to one or more neural networks. The signals enhance performance, efficiency, and/or security of one or more of the computing devices. DNNs can be dynamically trained to personalize operations by updating DNN weights or other parameters.
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13.发明申请公开(公告)号：US20200341114A1
公开(公告)日：2020-10-29
申请号：US16497968
申请日：2018-03-28
Applicant: SRI International
Inventor： Girish Acharya , Douglas Bercow , John Brian Burns , Bradley J. Clymer , Aaron J. Heller , Jeffrey Lubin , Bhaskar Ramamurthy , David Watters , Aravind Sundaresan
Abstract: An identification system includes a radar sensor configured to generate a time-domain or frequency-domain signal representative of electromagnetic waves reflected from one or more objects within a three-dimensional space over a period of time and a computation engine executing on one or more processors. The computation engine is configured to process the time-domain or frequency-domain signal to generate range and velocity data indicating motion by a living subject within the three-dimensional space. The computation engine is further configured to identify, based at least on the range and velocity data indicating the motion by the living subject, the living subject and output an indication of an identity of the living subject.
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公开(公告)号：US20200184718A1
公开(公告)日：2020-06-11
申请号：US16523313
申请日：2019-07-26
Applicant: SRI International
Inventor： Han-Pang Chiu , Supun Samarasekera , Rakesh Kumar , Bogdan C. Matei , Bhaskar Ramamurthy
Abstract: A method for providing a real time, three-dimensional (3D) navigational map for platforms includes integrating at least two sources of multi-modal and multi-dimensional platform sensor information to produce a more accurate 3D navigational map. The method receives both a 3D point cloud from a first sensor on a platform with a first modality and a 2D image from a second sensor on the platform with a second modality different from the first modality, generates a semantic label and a semantic label uncertainty associated with a first space point in the 3D point cloud, generates a semantic label and a semantic label uncertainty associated with a second space point in the 2D image, and fuses the first space semantic label and the first space semantic uncertainty with the second space semantic label and the second space semantic label uncertainty to create fused 3D spatial information to enhance the 3D navigational map.
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Patent Agency Ranking
公开(公告)号：US11740624B2
公开(公告)日：2023-08-29
申请号：US16639216
申请日：2018-08-17
Applicant: SRI International
Inventor： Bhaskar Ramamurthy , Supun Samarasekera , Thomas Low , Manish Kothari , John Peter Marcotullio , Jonathan Brookshire , Tobenna Arodiogbu , Usman Ghani
CPC classification number: G05D1/0022 , B60W60/001 , G05B17/02 , G05D1/0088 , G05D1/101 , G05D2201/0216
Abstract: A hybrid control system includes a control agent and a control engine. The control engine is configured to install a master plan to the control agent. The master plan includes a plurality of high-level tasks. The control agent is configured to operate according to the master plan to, for each high-level task of the high-level tasks, obtain one or more low-level controls and to perform the one or more low-level controls to realize the high-level task. The control agent is configured to operate according to the master plan to transition between the plurality of high-level tasks thereby causing a seamless transition between operating at least partially autonomously and operating at least partially based on input from the tele-operator, based at least on context for the control agent, to operate at least partially autonomously and at least partially based on input from the tele-operator during execution of the master plan.
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公开(公告)号：US20200227161A1
公开(公告)日：2020-07-16
申请号：US16744962
申请日：2020-01-16
Applicant: SRI International
Inventor： Mark Hanson , Bhaskar Ramamurthy , Manish Kothari , Brecken Hu Uhl
IPC: G16H40/20 , G16H10/60 , G16H70/20 , G16H50/30 , G06Q10/10 , G16H50/20 , G06F16/2458 , G06N20/00 , G10L15/02 , G10L15/22 , G10L15/00 , G10L25/63 , G10L15/18 , G10L25/66
Abstract: In general, this disclosure describes techniques for a health management system that schedules medical appointments based on a dialog with a user (e.g., a patient), clinical guideline information, and/or other information. The health management system may engage in a dialog with the user, the dialog including requests from the health management system for audio input to the user device and audio input from the user in response to each request. The health management system may extract information from the audio input and compare the extracted information to clinical guideline information to determine one or more probable health conditions of the user. The health management system may determine a time allotment, identify a health care provider type and a platform for a medical appointment based on the one or more probable health conditions.
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公开(公告)号：US20200013511A1
公开(公告)日：2020-01-09
申请号：US16503064
申请日：2019-07-03
Applicant: SRI International
Inventor： Massimiliano de Zambotti , Fiona C. Baker , Mohamad Forouzanfar , Bhaskar Ramamurthy , Laurie Menoud
Abstract: Embodiments in accordance with the present disclosure are directed to systems and methods for managing hot flashes and/or menopause symptoms. An example system includes sensor circuitry and logic circuitry. The sensor circuitry obtains a physical measurement associated with a user and communicates the physical measurement. The logic circuitry generates a predictive model that indicates a probability of the user having a hot flash at a date and time based on a plurality of input parameters, revises the probability based on the physical measurement using the predictive model, and communicates data indicative of an action in response to the revised probability being outside a threshold, such as providing cooling relief.
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公开(公告)号：US20190266514A1
公开(公告)日：2019-08-29
申请号：US16318667
申请日：2017-07-21
Applicant: SRI International
Abstract: A system comprises one or more observation stations. Each observation station of the one or more observation stations comprises a corresponding set of one or more sensors. Additionally, the system comprises one or more physical machines that implement a computation engine configured to receive first observation data from the one or more observation stations. The computation engine may use the first observation data to train a machine learning system. The computation engine may subsequently use the trained machine learning system to provide feedback regarding an additional instance of the observation subject. The computation engine outputs the feedback.
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19.发明申请公开(公告)号：US20170364792A1
公开(公告)日：2017-12-21
申请号：US15625578
申请日：2017-06-16
Applicant: SRI International
Inventor： Sek M. Chai , David C. Zhang , Mohamed R. Amer , Timothy J. Shields , Aswin Nadamuni Raghavan , Bhaskar Ramamurthy
CPC classification number: G06N3/0454 , G06F9/46 , G06F9/50 , G06N3/0445 , G06N3/063 , G06N3/08
Abstract: Operations of computing devices are managed using one or more deep neural networks (DNNs), which may receive, as DNN inputs, data from sensors, instructions executed by processors, and/or outputs of other DNNs. One or more DNNs, which may be generative, can be applied to the DNN inputs to generate DNN outputs based on relationships between DNN inputs. The DNNs may include DNN parameters learned using one or more computing workloads. The DNN outputs may be, for example, control signals for managing operations of computing devices, predictions for use in generating control signals, warnings indicating an acceptable state is predicted, and/or inputs to one or more neural networks. The signals enhance performance, efficiency, and/or security of one or more of the computing devices. DNNs can be dynamically trained to personalize operations by updating DNN weights or other parameters.
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