VIDEO ANNOTATION SYSTEM FOR DEEP LEARNING BASED VIDEO ANALYTICS

    公开(公告)号:US20220067381A1

    公开(公告)日:2022-03-03

    申请号:US17010795

    申请日:2020-09-02

    Abstract: A video annotation system for deep learning based video analytics and corresponding methods of use and operation are described that significantly improve the efficiency of video data frame labeling and the user experience. The video annotation system described herein may be deployed at a network edge and may support various intelligent annotation functionality including annotation tracking, adaptive video segmentation, and execution of predictive annotation algorithms. In addition, the video annotation system described herein supports team collaboration functionality in connection with large-scale labeling tasks.

    Access point availability prediction

    公开(公告)号:US10524195B2

    公开(公告)日:2019-12-31

    申请号:US15579516

    申请日:2015-06-04

    Abstract: In an example, a set of training fingerprints may be accessed, in which each of the training fingerprints specifies an access point of a plurality of access points to which a mobile device made a successful connection, a relative signal strength of the connection to the access point, and a cellular signal strength of a cellular tower near the mobile device when the successful connection to the access point was made. Level counts of the relative signal strengths of the connections to the access points corresponding to the cellular signal strengths of the cellular tower may be cumulated from the set of training fingerprints. The cumulated level counts of the relative signal strengths of the access points may be ranked.

    Predicting wireless access point availability

    公开(公告)号:US10455430B2

    公开(公告)日:2019-10-22

    申请号:US16081002

    申请日:2016-03-10

    Abstract: Examples relate to predicting wireless access point availability. In one example, a computing device may: generate, for a wireless access point, a mapping for predicting availability of the wireless access point, the mapping specifying: one or more in-range cellular towers to which at least one client device has been connected while the at least one client device was also connected to the wireless access point; one or more border cellular towers to which at least one client device has been connected to i) subsequent to being connected to one of the one or more in-range cellular towers, and ii) while not connected to the wireless access point; and one or more out-of-range cellular towers to which at least one client device has been connected to i) subsequent to being connected to one of the one or more border cellular lowers, and ii) while not connected to the wireless access point.

    Enterprise-based network selection

    公开(公告)号:US11382030B2

    公开(公告)日:2022-07-05

    申请号:US16071261

    申请日:2016-01-29

    Abstract: In some examples, a user equipment may perform a method that includes identifying that a first wireless network operated by an enterprise is accessible to the user equipment as well as identifying that a second wireless network different from the first wireless network and also operated by the enterprise is accessible to the user equipment. The method performed by the user equipment may further include selecting the first wireless network to connect to instead of the second wireless network based on an enterprise employee characteristic associated with the user equipment.

    Predicting available access points

    公开(公告)号:US10820294B2

    公开(公告)日:2020-10-27

    申请号:US15572064

    申请日:2015-03-09

    Abstract: Examples relate to predicting available access points. In one example, a computing device may: obtain a set of training fingerprints, each training fingerprint specifying, for a client device, i) a set of access points, and ii) cellular signal strength measurements for each cellular tower in a set of cellular towers; generate a plurality of classes based on the set of training fingerprints, each class specifying at least one access point, the access points of each class corresponding to the set of access points specified by at least one training fingerprint, and each combination being different from combinations specified by each other class in the plurality of classes; and train a predictive model to receive, as input, an input fingerprint specifying a cellular signal strength measurement for each cellular tower in a set of input cellular towers and produce, as output, at least one of the plurality of classes.

    Enable access point availability prediction

    公开(公告)号:US10271218B2

    公开(公告)日:2019-04-23

    申请号:US15579533

    申请日:2015-06-04

    Abstract: In an example, a set of training fingerprints may be access, in which each of the training fingerprints may specify an access point of a plurality of access points to which a mobile device made a successful connection and a cellular signal strength of a cellular tower near the client device when the successful connection was made. An interim model may be generated from the accessed set of training fingerprints, in which the interim model may contain a subset of the information in the set of training fingerprints to enable a destination device to generate a prediction model to predict an availability of an access point. The generated interim model may be transferred to the destination device.

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