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    EVENT LOG TAMPER RESISTANCE
    231.
    发明申请
    EVENT LOG TAMPER RESISTANCE 审中-公开

    公开(公告)号：WO2021069991A1

    公开(公告)日：2021-04-15

    申请号：PCT/IB2020/058764

    申请日：2020-09-21

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM UNITED KINGDOM LIMITED ,  IBM (CHINA) INVESTMENT COMPANY LIMITED

    Inventor： KUAN, Michael ,  BALLENTINE, Scott ,  SOFIA, Anthony, Thomas

    IPC: G06F21/64

    Abstract: Embodiments are described for generating, by the processor, a first event record in response to an event being performed by the computer and generating, by the processor, a first tamper resistance record in response to the first event record being generated. The first tamper resistance record includes a first signature is created based at least in part on the first event record and a second signature is created based at least in part on the first event record. Aspects also includes validating the first event record based on the first signature and the second signature in the first tamper resistance record in response to a request to detect tampering of the first event record.

    PREDICTING WEATHER RADAR IMAGES
    233.
    发明申请
    PREDICTING WEATHER RADAR IMAGES 审中-公开

    公开(公告)号：WO2021064524A1

    公开(公告)日：2021-04-08

    申请号：PCT/IB2020/058930

    申请日：2020-09-24

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM UNITED KINGDOM LIMITED ,  IBM (CHINA) INVESTMENT COMPANY LIMITED

    Inventor： TANG, Jingyin

    IPC: G06N3/08

    Abstract: Predicting weather radar images by building a first machine learning model to generate first predictive radar images based upon input weather forecast data, and a second machine learning model to generate second predictive radar images based upon historical radar images and the first predictive radar images. Further by generating enhanced predictive radar images by providing the first machine learning model weather forecast data for a location and time and providing the second machine learning model with historical radar images for the location and an output of the first machine learning model.

    SYSTEMS AND METHODS FOR TRAINING A MODEL USING A FEW-SHOT CLASSIFICATION PROCESS
    236.
    发明申请
    SYSTEMS AND METHODS FOR TRAINING A MODEL USING A FEW-SHOT CLASSIFICATION PROCESS 审中-公开

    公开(公告)号：WO2021059081A1

    公开(公告)日：2021-04-01

    申请号：PCT/IB2020/058543

    申请日：2020-09-15

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM UNITED KINGDOM LIMITED ,  IBM (CHINA) INVESTMENT COMPANY LIMITED

    Inventor： KARLINSKY, Leonid ,  SHTOK, Joseph

    IPC: G06K9/62

    Abstract: There is provided a method of computing a model for classification of a data element, comprising: feeding a plurality of labeled auxiliary data elements and at least one labeled relevant data elements for each of a plurality of relevant classification categories, into a synthesizer component, for outputting at least one synthetic labeled relevant data element for each one of the plurality of relevant classification categories, feeding the synthetic labeled relevant data elements and a plurality of unlabelled training relevant data elements into a domain adaptation component, for outputting a respective relevant classification category for each of the plurality of unlabelled training relevant data elements, iteratively end-to-end training the synthesis component and the domain adaptation component, and providing the trained domain adaption component, for outputting a relevant classification category in response to an input of a query unlabelled data element.

    SCALABLE STRUCTURE LEARNING VIA CONTEXT-FREE RECURSIVE DOCUMENT DECOMPOSITION
    238.
    发明申请
    SCALABLE STRUCTURE LEARNING VIA CONTEXT-FREE RECURSIVE DOCUMENT DECOMPOSITION 审中-公开

    公开(公告)号：WO2021053510A1

    公开(公告)日：2021-03-25

    申请号：PCT/IB2020/058572

    申请日：2020-09-15

    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION ,  IBM UNITED KINGDOM LIMITED ,  IBM (CHINA) INVESTMENT COMPANY LIMITED

    Inventor： GOYAL, Munish ,  ARYA, Avinash

    IPC: G06K9/20

    Abstract: An approach is provided in which a document is converted into a bitmap image and the processing method aggregates a set of pixel values from the bitmap image into a set of row sum values and a set of column sum values. The bitmap image being a pixelated representation of the document. The approach applies a localized Fourier transform to the set of row sum values and the set of column sum values to generate frequency representations of the set of row sum values and the set of frequency sum values. The approach decomposes the bitmap image into a set of image portions based on at least one separation location identified in the set of frequency representations, and sends the set of image portions to a text recognition system.

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