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    Method for object detection using knowledge distillation
    3.
    发明授权
    Method for object detection using knowledge distillation 有权

    公开(公告)号：US11755920B2

    公开(公告)日：2023-09-12

    申请号：US16808408

    申请日：2020-03-04

    申请人： CORTICA LTD.

    发明人： Igal Raichelgauz ,  Eli Passov

    IPC分类号： G06N3/088 ,  G06N3/045 ,  G06N3/048

    CPC分类号： G06N3/088 ,  G06N3/045 ,  G06N3/048

    摘要： A method that may include training a student ODNN to mimic a teacher ODNN. The training may include calculating a teacher student detection loss that is based on a pre-bounding-box output of the teacher ODNN. The pre-bounding-box output of the teacher ODNN is a function of pre-bounding-box outputs of different ODNNs that belong to the teacher ODNN. The method may also include detecting one or more objects in an image, by feeding the image to the trained student ODNN; outputting by the trained student ODNN a student pre-bounding-box output; and calculating one or more bounding boxes based on the student pre-bounding-box output.

    Determining object information that does not explicitly appear in a media unit signature
    8.
    发明授权
    Determining object information that does not explicitly appear in a media unit signature 有权

    公开(公告)号：US11132548B2

    公开(公告)日：2021-09-28

    申请号：US16808405

    申请日：2020-03-04

    申请人： CORTICA LTD.

    发明人： Igal Raichelgauz ,  Kirill Dyagilev

    IPC分类号： G06K9/00 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

    摘要： There may be provided a method for determining object information related to an object that appears in a media element, the method may include (a) receiving or generating a signature of the media element, wherein the signature may include identifiers, wherein the identifiers may include an object identifier related to the object, wherein the object identifier points to locations of output elements, within an output of a convolutional neural network, of elements of significance in relation to the object; (b) finding a group of contributing portions of the media element that had a significant contribution to the generation, by the convolutional neural network, of the output elements of significance in relation to the object; and (c) determining object information related to the object based on a distribution of the group of the contributing portions of the media element.

    Autonomous Grading of Gemstones
    9.
    发明申请
    Autonomous Grading of Gemstones 有权

    公开(公告)号：US20210148831A1

    公开(公告)日：2021-05-20

    申请号：US16942727

    申请日：2020-07-29

    申请人： Cortica Ltd.

    发明人： Igal Raichelgauz ,  Karina Odinaev

    IPC分类号： G01N21/87 ,  G01J3/46 ,  G01N21/95 ,  G01N33/38 ,  G06K9/46

    摘要： A method for grading a precious gem. The method may include generating, by a signature generator, a signature of the precious gem; searching, out of multiple concept structures, for a matching concept structures that comprises at least one reference signature that matches the signature of the precious gem; wherein each concept structure comprises precious gem signatures of the same grade; wherein at least two concept structures differ from each other by grade; wherein each concept structure is generated by applying an unsupervised learning process and associating a grade with the cluster; and determining the grade of the precious gem based on a grade associated with a matching concept structure.