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    SYSTEM AND METHOD TO REVIEW ONLINE VIOLENCE AND EDUCATION
    21.
    发明申请
    SYSTEM AND METHOD TO REVIEW ONLINE VIOLENCE AND EDUCATION 有权

    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.

    ERROR-BASED EXPLANATIONS FOR ARTIFICIAL INTELLIGENCE BEHAVIOR
    22.
    发明公开
    ERROR-BASED EXPLANATIONS FOR ARTIFICIAL INTELLIGENCE BEHAVIOR 审中-公开

    公开(公告)号：US20240005654A1

    公开(公告)日：2024-01-04

    申请号：US17656391

    申请日：2022-03-24

    Applicant: SRI International

    Inventor： Arijit Ray ,  Michael A. Cogswell ,  Ajay Divakaran ,  Yi Yao ,  Giedrius T. Burachas ,  Kamran Alipour

    IPC: G06V10/98 ,  G06T11/00 ,  G06V10/776 ,  G06V10/77

    CPC classification number: G06V10/98 ,  G06T11/001 ,  G06V10/776 ,  G06V10/7715

    Abstract: A computing system comprising a memory configured to store an artificial intelligence (AI) model and an image, and a computation engine executing one or more processors may be configured to perform the techniques for error-based explanations for AI behavior. The computation engine may execute the AI model to analyze the image to output a result. The AI model may, when analyzing the image to output the result, process, based on data indicative of the result, the image to assign an error score to each image feature extracted from the image, and obtain, based on the error scores, an error map. The AI model may next update, based on the error map and to obtain a first updated image, the image to visually indicate the error score assigned to each of the image features, and output one or more of the error scores, the error map, and the first updated image.

    Method and apparatus for correlating and viewing disparate data
    26.
    发明授权
    Method and apparatus for correlating and viewing disparate data 有权
    用于关联和查看不同数据的方法和装置

    公开(公告)号：US09563623B2

    公开(公告)日：2017-02-07

    申请号：US14718669

    申请日：2015-05-21

    Applicant: SRI International

    Inventor： Harpreet Sawhney ,  Jayakrishnan Eledath ,  Ajay Divakaran ,  Mayank Bansal ,  Hui Cheng

    IPC: G06F17/30 ,  G06F17/27

    CPC classification number: G06F17/2785 ,  G06F17/30047 ,  G06F17/30867 ,  G06F17/3087

    Abstract: Embodiments of the present invention are directed towards methods and apparatus for generating a common operating picture of an event based on the event-specific information extracted from data collected from a plurality of electronic information sources. In some embodiments, a method for generating a common operating picture of an event includes collecting data, comprising image data and textual data, from a plurality of electronic information sources, extracting information related to an event from the data, said extracted information comprising image descriptors, visual features, and categorization tags, by applying statistical analysis and semantic analysis, aligning the extracted information to generate aligned information, recognizing event-specific information for the event based on the aligned information, and generating a common operating picture of the event based on the event-specific information.

    Abstract translation: 本发明的实施例涉及用于基于从从多个电子信息源收集的数据中提取的事件特定信息来生成事件的公共操作画面的方法和装置。 在一些实施例中，用于生成事件的公共操作画面的方法包括从多个电子信息源收集包括图像数据和文本数据的数据，从数据中提取与事件相关的信息，所述提取的信息包括图像描述符 ，视觉特征和分类标签，通过应用统计分析和语义分析，对齐提取的信息以产生对齐的信息，基于对准的信息识别事件的事件特定信息，以及基于对象信息生成事件的公共操作画面 事件特定信息。

    METHOD AND APPARATUS FOR CORRELATING AND VIEWING DISPARATE DATA
    27.
    发明申请
    METHOD AND APPARATUS FOR CORRELATING AND VIEWING DISPARATE DATA 有权
    用于查询和查看不同数据的方法和装置

    公开(公告)号：US20150254231A1

    公开(公告)日：2015-09-10

    申请号：US14718669

    申请日：2015-05-21

    Applicant: SRI International

    Inventor： Harpreet Sawhney ,  Jayakrishnan Eledath ,  Ajay Divakaran ,  Mayank Bansal ,  Hui Cheng

    IPC: G06F17/27 ,  G06F17/30

    CPC classification number: G06F17/2785 ,  G06F17/30047 ,  G06F17/30867 ,  G06F17/3087

    Abstract: A computer-implemented method comprising collecting data from a plurality of information sources, identifying a geographic location associated with the data and forming a corresponding event according to the geographic location, correlating the data and the event with one or more topics based at least partly on the identified geographic location and storing the correlated data and event and inferring the associated geographic location if the data does not comprise explicit location information, including matching the data against a database of geo-referenced data.

    Abstract translation: 一种计算机实现的方法，包括从多个信息源收集数据，识别与所述数据相关联的地理位置并根据所述地理位置形成对应的事件，至少部分地基于所述数据和所述事件与一个或多个主题相关联 所识别的地理位置并存储相关数据和事件，并且如果数据不包括显式位置信息，则推断相关联的地理位置，包括将数据与地理参考数据的数据库进行匹配。

    Analysis and design of dynamical system controllers using neural differential equations
    29.
    发明授权
    Analysis and design of dynamical system controllers using neural differential equations 有权

    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.

    Zero-shot object detection
    30.
    发明授权
    Zero-shot object detection 有权

    公开(公告)号：US11610384B2

    公开(公告)日：2023-03-21

    申请号：US17337093

    申请日：2021-06-02

    Applicant: SRI International

    Inventor： Karan Sikka ,  Ajay Divakaran ,  Ankan Bansal

    IPC: G06V10/22 ,  G06K9/62 ,  G06N20/00 ,  G06N5/04 ,  G06T11/20 ,  G06V10/40 ,  G06V10/20 ,  G06V20/10 ,  G06V30/262 ,  G06V10/75

    Abstract: A method, apparatus and system for zero shot object detection includes, in a semantic embedding space having embedded object class labels, training the space by embedding extracted features of bounding boxes and object class labels of labeled bounding boxes of known object classes into the space, determining regions in an image having unknown object classes on which to perform object detection as proposed bounding boxes, extracting features of the proposed bounding boxes, projecting the extracted features of the proposed bounding boxes into the space, computing a similarity measure between the projected features of the proposed bounding boxes and the embedded, extracted features of the bounding boxes of the known object classes in the space, and predicting an object class label for proposed bounding boxes by determining a nearest embedded object class label to the projected features of the proposed bounding boxes in the space based on the similarity measures.

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