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US Patent 10360481 Unconstrained event monitoring via a network of drones

Patent 10360481 was granted and assigned to AT&T Intellectual Property I on July, 2019 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
AT&T Intellectual Property I
AT&T Intellectual Property I
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Current Assignee
AT&T Intellectual Property I
AT&T Intellectual Property I
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
103604810
Patent Inventor Names
Raghuraman Gopalan0
Date of Patent
July 23, 2019
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Patent Application Number
155985620
Date Filed
May 18, 2017
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Patent Citations Received
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US Patent 11509812 Facilitation of collaborative camera field of view mapping
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US Patent 11368991 Facilitation of prioritization of accessibility of media
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US Patent 11411757 Facilitation of predictive assisted access to content
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US Patent 11956841 Facilitation of prioritization of accessibility of media
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US Patent 12075197 Facilitation of collaborative monitoring of an event
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US Patent 11611448 Facilitation of predictive assisted access to content
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US Patent 11768082 Facilitation of predictive simulation of planned environment
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US Patent 11356349 Adaptive resource allocation to facilitate device mobility and management of uncertainty in communications
Patent Primary Examiner
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Li Liu
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Patent abstract

In one example, the present disclosure describes a device, computer-readable medium, and method for performing event monitoring in an unconstrained manner using a network of drones. For instance, in one example, a first video and a second video are obtained. The first video is captured by a first drone monitoring a first field of view of a scene, while the second video is captured by a second drone monitoring a second field of view of the scene. Both the first video and the second video are unlabeled. A deep learning technique is applied to the first video and the second video to learn a model of the scene. The model identifies a baseline for the scene, and the deep learning technique is unsupervised. The model is stored.

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