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公开(公告)号：US20210117835A1
公开(公告)日：2021-04-22
申请号：US16654277
申请日：2019-10-16
摘要： Techniques for enhancing strategic patrol planning and dispatch decision making based on gone on arrival prediction are provided. In one aspect, a crime prediction map may be retrieved. The crime prediction map may include incident locations and incident times, of predicted incidents occurring within a geographic area. The predictions may be based on historical data, the historical data including data from a computer aided dispatch (CAD) system. For each predicted incident location and incident time, a probability of gone on arrival (GOA) incident disposition may be calculated for a plurality of responder response times. The probability may be calculated based on the historical data from the CAD system.
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公开(公告)号：US20190197354A1
公开(公告)日：2019-06-27
申请号：US15851761
申请日：2017-12-22
CPC分类号： G06K9/6256 , G06F16/489 , G06K9/00711 , G06K9/209 , G06K9/78 , G06K2009/00738 , G06N3/04 , G06N3/0445 , G06N3/08 , G08B13/194 , G08B29/20 , H04N7/18 , H04N7/181 , H04N7/188
摘要： Receive first context information including sensor information values from in-field sensors and a time associated with a capture of the first context information. Access a context to detectable event mapping that maps sets of sensor information values to events and identify a particular event associated with the received first context information. Determine a geographic location associated with the in-field sensors and access an imaging camera location database and identify particular imaging cameras that have a field of view including the determined geographic location during the time associated with the capture of the first context information. Retrieve audio and/or video streams captured by the particular imaging cameras, identify machine learning training modules corresponding to machine learning models for detecting the particular event in audio and/or video streams, and provide the audio and/or video streams to the machine learning training modules for further training of the corresponding machine learning models.
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3.发明申请公开(公告)号：US20220171986A1
公开(公告)日：2022-06-02
申请号：US17107980
申请日：2020-12-01
发明人： NICHOLAS ALCOCK , ERIC PETERSON , SHAUN MARLATT , LIIA FADEEVA , KEVIN PIETTE , BRENNA RANDLETT , QUAN PAN , HUGO FITZPATRICK , JEHAN WICKRAMASURIYA
摘要： Obtaining potential match results for a reference image across a plurality of system sites is disclosed. A computing device of one of the system sites includes a signature generator identifiable as a first version amongst a plurality of versions of a respective plurality of possible signature generators. The computing device is configured to generate, within the first signature generator, a first signature corresponding to a cropped object portion of a larger image. The first signature is distinctive to the first version. The computing device is further configured to determine that the cropped object portion being processed within the computing device is a match result for a similar images search. A server is configured to receive the cropped object portion and the first signature from the computing device.
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公开(公告)号：US20220100798A1
公开(公告)日：2022-03-31
申请号：US17034285
申请日：2020-09-28
IPC分类号： G06F16/835 , G06Q50/26 , G06N3/04 , G06N3/08 , G06F21/53 , G06F40/284 , G06F40/205
摘要： A method of processing a query to a database from a query source is provided, comprising: receiving the query, the query in a first format supported by the query source; inputting the query into a first neural network; outputting, by the first neural network, the query in a second format, wherein the second format is a format supported by the database; receiving, from the database, a response to the query, the response in the second format; inputting the response to the query into a second neural network; outputting, by the second neural network, the response to the query in the first format; wherein each neural network is trained by inputting a first plurality of pairs of semi-structured data, each pair of semi-structured data comprising a sample query or response in the first format and the sample query or response in the second format.
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公开(公告)号：US20190197369A1
公开(公告)日：2019-06-27
申请号：US15851760
申请日：2017-12-22
CPC分类号： G06K9/66 , G06K9/00624 , G06K9/0063 , G06K9/00771 , G06K9/6262 , G06N3/04 , G06N3/08 , G06N3/082 , G06N5/003 , G06N20/10 , H04N5/247 , H04N7/181
摘要： Receive first context information (FCI) including entered in-field incident timeline information values from an in-field incident timeline application and a time associated with an entry of the FCI values. Access a mapping that maps in-field incident timeline information values to events having a pre-determined threshold confidence of occurring and identify an event associated with the received FCI. Determine a location associated with the entry of the FCI and a time period associated with the entry of the FCI. Access a camera location database and identify cameras that have a field of view including the location during the time period. Retrieve audio and/or video streams captured by the cameras during the time period. And provide the audio and/or video streams to machine learning training modules corresponding to machine learning models for detecting the event in and/or video streams for further training of the machine learning models.
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