Database comparison operation to identify an object

    公开(公告)号:US10956493B2

    公开(公告)日:2021-03-23

    申请号:US15570878

    申请日:2015-05-19

    Abstract: Examples disclosed herein relate to a database comparison operation to identify an object. For example, a processor may enroll a set of object templates in a storage based on objects within input content and enroll a target object template in the storage based on a target object in target content. The processor may identify an object within the input content associated with the target object based on a database comparison operation of the stored set of object templates to the stored target object template. The processor may output object recognition information related to the identified object.

    Dynamic function invocation
    12.
    发明授权

    公开(公告)号:US10936592B2

    公开(公告)日:2021-03-02

    申请号:US15565521

    申请日:2015-04-30

    Abstract: According to an example, dynamic function invocation may include ascertaining a query for a database management system (DBMS). Dynamic function invocation may further include implementing a dynamic function as a meta user defined function to invoke a plurality of different coded functions including a coded function that is to be invoked by the query to perform an operation related to the DBMS, and executing the dynamic function by the query to load and invoke the coded function to perform the operation related to the DBMS.

    MOBILE DEVICE LOCATOR
    14.
    发明申请

    公开(公告)号:US20210011111A1

    公开(公告)日:2021-01-14

    申请号:US17030673

    申请日:2020-09-24

    Abstract: Examples herein involve estimating a first position of a mobile device based on first communication signals, assigning a first set of particles to a number of respective first sampling locations within a threshold distance of the first position, adjusting the assignment of the first set of particles to second sampling locations based on movement of the mobile device, and estimating a second position of the mobile device based on the second sampling locations.

    MACHINE LEARNING-BASED NETWORK DEVICE PROFILING

    公开(公告)号:US20200382527A1

    公开(公告)日:2020-12-03

    申请号:US16428422

    申请日:2019-05-31

    Abstract: A method includes applying, by a computer, supervised machine learning to classify a network device that is associated with a security event occurring in a computer system based on data representing features of the network device. The security event is associated with a potential security threat to the computer system, and the classification of the network device by the supervised machine learning is associated with a confidence. The technique includes, in response to the confidence being below a threshold, applying an active machine learning classifier to the data to learn a classification for the data and using the classification learned by the active machine learning classifier to adapt the supervised machine learning to recognize the classification.

    MAPPING BETWEEN RAW ANOMALY SCORES AND TRANSFORMED ANOMALY SCORES

    公开(公告)号:US20200379863A1

    公开(公告)日:2020-12-03

    申请号:US16426850

    申请日:2019-05-30

    Abstract: In some examples, a system is to, given an anomaly score threshold over which at least one anomalous point is to be observed in a test set of points with a specified probability, determine, using raw anomaly scores for a training set of points, a first mapping between raw anomaly scores in a first range and first transformed anomaly scores using a first transformation technique. The system is to determine, using the raw anomaly scores for the training set of points, a second mapping between raw anomaly scores in a second range greater than the first range and second transformed anomaly scores using a second transformation technique different from the first transformation technique. The system is to use the first mapping and the second mapping to detect an anomaly in a computing environment based on the test set of points.

    SOURCE ENTITIES OF SECURITY INDICATORS
    17.
    发明申请

    公开(公告)号:US20200351292A1

    公开(公告)日:2020-11-05

    申请号:US16076274

    申请日:2016-02-12

    Abstract: Examples disclosed herein relate to source entities of security indicators. Some examples disclosed herein enable identifying, in a security information sharing platform, a security indicator that is originated from a source entity where the security indicator comprises an observable. Some examples further enable determining a reliability level of the source entity based on at least one of: security events, sightings of the observable, a first set of user feedback information that is submitted for the security indicator by users of the security information sharing platform, or a second set of user feedback information that is collected from external resources that are external to the security information sharing platform.

    COMPARABLE USER INTERFACE OBJECT IDENTIFICATIONS

    公开(公告)号:US20200310952A1

    公开(公告)日:2020-10-01

    申请号:US16086176

    申请日:2016-03-23

    Abstract: Example implementations relate to comparable UI object identifications. Some implementations may include a data capture engine to capture data points during test executions of the application under test. The data points may include, for example, test action data and application action data. Additionally, some implementations may include a data correlation engine to correlate each of the data points with a particular test execution of the test executions, and each of the data points may be correlated based on a sequence of events that occurred during the particular test execution. Furthermore, some implementations may also automatically identify, based on the correlated data points, a set of comparable UI objects.

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