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    SIGNATURE GENERATION FOR MULTIMEDIA DEEP-CONTENT-CLASSIFICATION BY A LARGE-SCALE MATCHING SYSTEM AND METHOD THEREOF
    171.
    发明申请
    SIGNATURE GENERATION FOR MULTIMEDIA DEEP-CONTENT-CLASSIFICATION BY A LARGE-SCALE MATCHING SYSTEM AND METHOD THEREOF 有权
    通过大规模匹配系统进行多媒体深度分类的签名生成及其方法

    公开(公告)号：US20130080433A1

    公开(公告)日：2013-03-28

    申请号：US13682132

    申请日：2012-11-20

    Applicant: Cortica, Ltd.

    Inventor： Igal RAICHELGAUZ ,  Karina ORDINAEV ,  Yehoshua Y. ZEEVI

    IPC: G06F17/30

    CPC classification number: G06F17/30595 ,  G06F17/3002 ,  G06F17/30026 ,  G06F17/30047 ,  G06F17/30743 ,  G06F17/30746 ,  G06F17/30787 ,  G06F17/30796 ,  G06F17/30799 ,  G06K9/00744 ,  G10L15/26 ,  G10L15/265 ,  G10L15/32

    Abstract: Content-based clustering, recognition, classification and search of high volumes of multimedia data in real-time. The embodiments disclosed herein are dedicated to real-time fast generation of signatures to high-volume of multimedia content-segments, based on relevant audio and visual signals, and to scalable matching of signatures of high-volume database of content-segments' signatures. The embodiments disclosed herein can be implemented in any applications which involve large-scale content-based clustering, recognition and classification of multimedia data, such as, content-tracking, video filtering, multimedia taxonomy generation, video fingerprinting, speech-to-text, audio classification, object recognition, video search and any other application requiring content-based signatures generation and matching for large content volumes such as, web and other large-scale databases.

    Abstract translation: 基于内容的聚类，识别，分类和实时搜索大量的多媒体数据。 本文公开的实施例专用于基于相关音频和视觉信号对大量多媒体内容片段进行签名的实时快速生成，以及内容片段签名的大容量数据库的签名的可缩放匹配。 本文公开的实施例可以在涉及基于大规模内容的聚类，多媒体数据的识别和分类的任何应用中实现，诸如内容跟踪，视频过滤，多媒体分类生成，视频指纹识别，语音对文本， 音频分类，对象识别，视频搜索和任何其他需要基于内容的签名生成和匹配大型内容卷（如Web和其他大型数据库）的应用程序。

    ISOLATING UNIQUE AND REPRESENTATIVE PATTERNS OF A CONCEPT STRUCTURE
    174.
    发明申请
    ISOLATING UNIQUE AND REPRESENTATIVE PATTERNS OF A CONCEPT STRUCTURE 有权

    公开(公告)号：US20220392197A1

    公开(公告)日：2022-12-08

    申请号：US17805855

    申请日：2022-06-07

    Applicant: Cortica Ltd.

    Inventor： Karina Odinaev

    IPC: G06V10/762 ,  G06V10/74

    Abstract: Systems, and method and computer readable media that store instructions for obtaining a first group concept structure that comprises first identifiers of first objects that belong to a first group; obtaining a second group concept structure that comprises second identifiers of second objects that belong to a second group; wherein the first identifiers were generated by processing media units that captured the first objects; wherein the second identifiers were generated by processing media units that captured the second objects; searching for shared pattern segments, each shared pattern segment appears in at least one first identifier and at least one second identifier; wherein a single shared pattern segment is indicative of a match; wherein a single non-shared pattern segment is suffice to represent a match; and responding to a finding of one or more shared pattern segments.

    System and method for determining common patterns in multimedia content elements based on key points
    175.
    发明授权
    System and method for determining common patterns in multimedia content elements based on key points 有权

    公开(公告)号：US11195043B2

    公开(公告)日：2021-12-07

    申请号：US15455363

    申请日：2017-03-10

    Applicant: Cortica, Ltd.

    Inventor： Dan Elharrar ,  Marco Rossi

    IPC: G06K9/46 ,  G06K9/00

    Abstract: A system and method for method for determining common patterns based on key points in multimedia data elements (MMDEs). The method includes: identifying a plurality of candidate key points in each of the plurality of MMDEs, wherein a size of each candidate key point is equal to a predetermined size and a scale of each candidate key point is equal to a predetermined scale; analyzing the identified candidate key points to determine a set of properties for each candidate key point; comparing the sets of properties of the plurality of candidate key points of each MMDE; selecting, for each MMDE, a plurality of key points from among the candidate key points based on the comparison; generating, based on the key points for each MMDE, a signature for the MMDE; and comparing the signatures of the plurality of MMDEs to output at least one common pattern among the plurality of MMDEs.

    Method for object detection using shallow neural networks
    180.
    发明授权
    Method for object detection using shallow neural networks 有权

    公开(公告)号：US10789527B1

    公开(公告)日：2020-09-29

    申请号：US16681885

    申请日：2019-11-13

    Applicant: Cortica LTD.

    Inventor： Igal Raichelgauz ,  Roi Saida

    IPC: G06N3/04 ,  G06T11/20 ,  G06K9/00 ,  G06N20/00

    Abstract: A method that may include feeding an input image and downscaled versions of the input image to multiple branches of an object detector calculating, by the multiple branches, candidate bounding boxes; and selecting bounding boxes. The multiple branches comprise multiple shallow neural networks that are followed by multiple region units. Each branch includes a shallow neural network and a region unit. The multiple shallow neural networks are multiple instances of a single trained shallow neural network. The single trained shallow neural network is trained to detect objects having a size that is within a predefined size range and to ignore objects having a size that is outside the predefined size range.

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