公开(公告)号：US20240312129A1

公开(公告)日：2024-09-19

申请号：US18509024

申请日：2023-11-14

Applicant: SRI International

Inventor： Anirban Roy ,  Adam Derek Cobb ,  Daniel Elenius ,  Patrick Denis Lincoln ,  Susmit Jha

IPC: G06T17/00 ,  G06V10/426

CPC classification number: G06T17/00 ,  G06V10/426

Abstract: In an example, a method for adapting a machine learning model includes receiving a digital representation of a three-dimensional (3D) object; learning, using a surrogate model, relationships between a plurality of points on a surface of the 3D object; and generating, using the surrogate model, one or more predictions about fluid properties along the surface of the 3D object.

公开(公告)号：US20240143689A1

公开(公告)日：2024-05-02

申请号：US18489777

申请日：2023-10-18

Applicant: SRI International

Inventor： Susmit Jha ,  Adam Derek Cobb ,  Anirban Roy ,  Daniel Elenius ,  Patrick Denis Lincoln

IPC: G06F17/11

CPC classification number: G06F17/11

Abstract: In an example, a method of designing a system or architecture includes, receiving a plurality of parameter values and a set of requirements for a plurality of objective functions related to a design problem; compressing the plurality of parameters to generate a latent representation; forward processing, with one or more Invertible Neural Networks (INNs), the latent representation to generate a plurality of objective values corresponding to the plurality of the objective functions; inverse processing the plurality of objective values; and generating, based on the latent representation, a plurality of solutions to the design problem that satisfy the set of requirements for the plurality of objective functions.

公开(公告)号：US20240414394A1

公开(公告)日：2024-12-12

申请号：US18737444

申请日：2024-06-07

Applicant: SRI International

Inventor： Claire Christensen ,  Anirban Roy ,  Ajay Divakaran ,  Todd Grindal

IPC: H04N21/44 ,  H04N21/439

Abstract: A computing system is configured to obtain a video that includes text elements and visual elements. The computing system is further configured to generate a plurality of text tokens representative of audio spoken in the video and a plurality of frame tokens representative of one or more frames of the video. The computing system is further configured to generate a set of features that includes a text feature, a frame feature, and a multi-modal feature, wherein the multi-modal feature is representative of multi-modal elements of the video, and wherein generating the set of features is based on the plurality of text tokens and the plurality of frame tokens. The computing system is further configured to associate the set of features with one or more labels to generate a multi-label classification of the video. The computing system is further configured to output an indication of the multi-label classification of the video.

公开(公告)号：US20230289498A1

公开(公告)日：2023-09-14

申请号：US17654737

申请日：2022-03-14

Applicant: SRI International ,  OBAYASHI CORPORATION ,  Hypar Inc.

Inventor： Anirban Roy ,  Jihua Huang ,  Sujeong Kim ,  Min Yin ,  Chih-hung Yeh ,  Takuma Nakabayshi ,  Yoshito Tsuji ,  Ian Keough ,  Matthew Campbell

IPC: G06F30/27 ,  G06T3/00 ,  G06V10/764 ,  G06V10/774 ,  G06F30/13

CPC classification number: G06F30/27 ,  G06T3/00 ,  G06V10/764 ,  G06V10/774 ,  G06F30/13

Abstract: In general, the disclosure describes techniques for parameterizing building information using images. In an example, a method includes receiving an image of a building; applying, by a machine learning system, a machine learning model to the received image of a building to generate, for a new building, new building parameters to be input to a building information modeling (BIM) data generation system, wherein the machine learning model is trained using images of buildings and corresponding building parameters for the buildings; and outputting, by the machine learning system, the new building parameters for the new building.

公开(公告)号：US20210192972A1

公开(公告)日：2021-06-24

申请号：US17129541

申请日：2020-12-21

Applicant: SRI International

Inventor： Girish Acharya ,  Louise Yarnall ,  Anirban Roy ,  Michael Wessel ,  Yi Yao ,  John J. Byrnes ,  Dayne Freitag ,  Zachary Weiler ,  Paul Kalmar

IPC: G09B19/00 ,  G06K9/72 ,  G10L15/18 ,  G06K9/00 ,  G10L25/57 ,  G06K9/62 ,  G09B5/06 ,  G06N20/00

Abstract: This disclosure describes machine learning techniques for capturing human knowledge for performing a task. In one example, a video device obtains video data of a first user performing the task and one or more sensors generate sensor data during performance of the task. An audio device obtains audio data describing performance of the task. A computation engine applies a machine learning system to correlate the video data to the audio data and sensor data to identify portions of the video, sensor, and audio data that depict a same step of a plurality of steps for performing the task. The machine learning system further processes the correlated data to update a domain model defining performance of the task. A training unit applies the domain model to generate training information for performing the task. An output device outputs the training information for use in training a second user to perform the task.

公开(公告)号：US12236330B2

公开(公告)日：2025-02-25

申请号：US17331150

申请日：2021-05-26

Applicant: SRI International

Inventor： Ajay Divakaran ,  Anirban Roy ,  Susmit Jha

IPC: G06N3/04 ,  G06F18/214 ,  G06N3/08 ,  G06N3/084 ,  G06V10/764 ,  G06V10/82

Abstract: In general, the disclosure describes techniques for characterizing a dynamical system and a neural ordinary differential equation (NODE)-based controller for the dynamical system. An example analysis system is configured to: obtain a set of parameters of a NODE model used to implement the NODE-based controller, the NODE model trained to control the dynamical system; determine, based on the set of parameters, a system property of a combined system comprising the dynamical system and the NODE-based controller, the system property comprising one or more of an accuracy, safety, reliability, reachability, or controllability of the combined system; and output the system property to modify one or more of the dynamical system or the NODE-based controller to meet a required specification for the combined system.

公开(公告)号：US20240169129A1

公开(公告)日：2024-05-23

申请号：US18512812

申请日：2023-11-17

Applicant: SRI International

Inventor： Adam Derek Cobb ,  Daniel Elenius ,  Anirban Roy ,  Patrick Denis Lincoln ,  Susmit Jha

IPC: G06F30/27

CPC classification number: G06F30/27 ,  G06F2119/02

Abstract: In an example, an iterative method for generating designs includes receiving, by a computing system, a plurality of symbolic rules and a plurality of design objectives for a design of a system; generating, by the computing system, a first plurality of designs for the system based on the plurality of the symbolic rules; evaluating performance of the first plurality of designs; training a machine learning model using the first plurality of designs and performance metrics; generating a second plurality of designs; evaluating, by the computing system, using a machine learning model, performance of the second plurality of designs to filter one or more designs that meet one or more of the plurality of the design objectives; evaluating performance of the filtered designs; and updating, by the computing system, the plurality of the design objectives and/or the plurality of the symbolic rules based on the evaluated performance of the filtered designs.

公开(公告)号：US20210374531A1

公开(公告)日：2021-12-02

申请号：US17331150

申请日：2021-05-26

Applicant: SRI International

Inventor： Ajay Divakaran ,  Anirban Roy ,  Susmit Jha

IPC: G06N3/08 ,  G06K9/62

Abstract: In general, the disclosure describes techniques for characterizing a dynamical system and a neural ordinary differential equation (NODE)-based controller for the dynamical system. An example analysis system is configured to: obtain a set of parameters of a NODE model used to implement the NODE-based controller, the NODE model trained to control the dynamical system; determine, based on the set of parameters, a system property of a combined system comprising the dynamical system and the NODE-based controller, the system property comprising one or more of an accuracy, safety, reliability, reachability, or controllability of the combined system; and output the system property to modify one or more of the dynamical system or the NODE-based controller to meet a required specification for the combined system.

公开(公告)号：US11210572B2

公开(公告)日：2021-12-28

申请号：US16717497

申请日：2019-12-17

Applicant: SRI International

Inventor： Ajay Divakaran ,  Karan Sikka ,  Karuna Ahuja ,  Anirban Roy

IPC: G06K9/62 ,  G06K9/46 ,  G06K9/72 ,  G06N3/08 ,  G06K9/66

Abstract: A method, apparatus and system for understanding visual content includes determining at least one region proposal for an image, attending at least one symbol of the proposed image region, attending a portion of the proposed image region using information regarding the attended symbol, extracting appearance features of the attended portion of the proposed image region, fusing the appearance features of the attended image region and features of the attended symbol, projecting the fused features into a semantic embedding space having been trained using fused attended appearance features and attended symbol features of images having known descriptive messages, computing a similarity measure between the projected, fused features and fused attended appearance features and attended symbol features embedded in the semantic embedding space having at least one associated descriptive message and predicting a descriptive message for an image associated with the projected, fused features.

公开(公告)号：US12118773B2

公开(公告)日：2024-10-15

申请号：US17129541

申请日：2020-12-21

Applicant: SRI International

Inventor： Girish Acharya ,  Louise Yarnall ,  Anirban Roy ,  Michael Wessel ,  Yi Yao ,  John J. Byrnes ,  Dayne Freitag ,  Zachary Weiler ,  Paul Kalmar

IPC: G06V10/82 ,  G06F18/22 ,  G06N20/00 ,  G06V20/20 ,  G06V20/40 ,  G06V30/19 ,  G06V30/262 ,  G06V40/10 ,  G06V40/20 ,  G09B5/06 ,  G09B19/00 ,  G10L15/18 ,  G10L25/57

CPC classification number: G06V10/82 ,  G06F18/22 ,  G06N20/00 ,  G06V20/20 ,  G06V20/41 ,  G06V30/19173 ,  G06V30/274 ,  G06V40/10 ,  G06V40/113 ,  G06V40/28 ,  G09B5/065 ,  G09B19/003 ,  G10L15/1815 ,  G10L25/57

Abstract: This disclosure describes machine learning techniques for capturing human knowledge for performing a task. In one example, a video device obtains video data of a first user performing the task and one or more sensors generate sensor data during performance of the task. An audio device obtains audio data describing performance of the task. A computation engine applies a machine learning system to correlate the video data to the audio data and sensor data to identify portions of the video, sensor, and audio data that depict a same step of a plurality of steps for performing the task. The machine learning system further processes the correlated data to update a domain model defining performance of the task. A training unit applies the domain model to generate training information for performing the task. An output device outputs the training information for use in training a second user to perform the task.