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公开(公告)号：US20210042532A1
公开(公告)日：2021-02-11
申请号：US16708648
申请日：2019-12-10
Applicant: Cisco Technology, Inc.
Inventor： Hugo Latapie , Enzo Fenoglio , David Delano Ward , Guillaume Sauvage De Saint Marc , Carole Gridley
Abstract: In one embodiment, a video analysis service receives video data captured by one or more cameras at a particular location. The service applies a neural network-based model to portions of the video data, to identify objects within the video data. The service maps outputs of the neural network-based model to symbols using a conceptual space. The outputs of the model comprise the identified objects. The service applies a symbolic reasoning engine to the symbols, to generate an alert. The service sends the alert to a user interface in conjunction with the video data.
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公开(公告)号：US20200068041A1
公开(公告)日：2020-02-27
申请号：US16666518
申请日：2019-10-29
Applicant: Cisco Technology, Inc.
Inventor： Hugo Latapie , Enzo Fenoglio , Plamen Nedeltchev , Manikandan Kesavan , Joseph Friel
Abstract: In one embodiment, a device in a network monitors a plurality of traffic flows in the network. The device extracts a plurality of features from the monitored plurality of traffic flows. The device generates a context model by using deep learning and reinforcement learning on the plurality of features extracted from the monitored traffic flows. The device applies the context model to a particular traffic flow associated with a client, to determine a context for the particular traffic flow. The device personalizes data sent to the client from a remote source based on the determined context.
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公开(公告)号：US20190325060A1
公开(公告)日：2019-10-24
申请号：US15960957
申请日：2018-04-24
Applicant: Cisco Technology, Inc.
Inventor： Enzo Fenoglio , Hugo Latapie , Angelo Fienga
Abstract: In one embodiment, a service in a network performs machine learning-based clustering of sensor data from a plurality of sensors in the network, to form sensor data clusters. The service maps the data clusters to symbolic clusters using a geometric conceptual space. The service infers a domain specific language from the symbolic clusters and from a domain specific ontology. The service performs, based on a query structured using the domain specific language, a lookup using the domain specific ontology to form a query response. The service sends the query response that comprises a result of the performed lookup via the network.
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公开(公告)号：US20190306011A1
公开(公告)日：2019-10-03
申请号：US16429177
申请日：2019-06-03
Applicant: Cisco Technology, Inc.
Inventor： Enzo Fenoglio , Hugo Latapie , David Delano Ward , Sawsen Rezig , Raphaël Wouters , Didier Colens , Donald Mark Allen , Dmitri Goloubev
Abstract: In one embodiment, a service that monitors a network detects a plurality of anomalies in the network. The service uses data regarding the detected anomalies as input to one or more machine learning models. The service maps, using a conceptual space, outputs of the one or more machine learning models to symbols. The service applies a symbolic reasoning engine to the symbols, to rank the anomalies. The service sends an alert for a particular one of the detected anomalies to a user interface, based on its corresponding rank.
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公开(公告)号：US09749718B1
公开(公告)日：2017-08-29
申请号：US15215098
申请日：2016-07-20
Applicant: Cisco Technology, Inc.
Inventor： Joseph Friel , Hugo Latapie , Andre Surcouf , Enzo Fenoglio
Abstract: Disclosed are systems, methods, and computer-readable storage media for adaptive telemetry based on in-network cross domain intelligence. A telemetry server can receive at least a first telemetry data stream and a second telemetry data stream. The first telemetry data stream can provide data collected from a first data source and the second telemetry data stream can provide data collected from a second data source. The telemetry server can determine correlations between the first telemetry data stream and the second telemetry data stream that indicate redundancies between data included in the first telemetry data stream and the second telemetry data stream, and then adjust, based on the correlations between the first telemetry data stream and the second telemetry data stream, data collection of the second telemetry data stream to reduce redundant data included in the first telemetry data stream and the second telemetry data stream.
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Patent Agency Ranking
公开(公告)号：US20240135709A1
公开(公告)日：2024-04-25
申请号：US17971268
申请日：2022-10-20
Applicant: Cisco Technology, Inc.
Inventor： Hugo Latapie , Ozkan Kilic , Adam James Lawrence , Gaowen Liu , Ramana Rao V. R. Kompella
Abstract: In one embodiment, a device represents spatial characteristics over time of an object in video data as one or more timeseries. The device detects an event based on a rate of change of behavioral regimes associated with different portions of the one or more timeseries. The device selects contextual data for the event that comprises spatial timeseries information for different types of objects or different activities. The device provides an alert for the event to a user interface regarding the event that includes the contextual data.
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公开(公告)号：US11715304B2
公开(公告)日：2023-08-01
申请号：US17860962
申请日：2022-07-08
Applicant: Cisco Technology, Inc.
Inventor： Hugo Latapie , Enzo Fenoglio , David Delano Ward , Guillaume Sauvage De Saint Marc , Carole Gridley
CPC classification number: G06V20/52 , G06Q30/0625 , G06T7/11 , G06T7/20 , G06V20/46 , G06V40/10 , G08B5/22 , H04N7/181 , G06T2207/10016 , G06T2207/20084 , G06T2207/30232 , G06V2201/08
Abstract: In one embodiment, a video analysis service receives video data captured by one or more cameras at a particular location. The service applies a neural network-based model to portions of the video data, to identify objects within the video data. The service maps outputs of the neural network-based model to symbols using a conceptual space. The outputs of the model comprise the identified objects. The service applies a symbolic reasoning engine to the symbols, to generate an alert. The service sends the alert to a user interface in conjunction with the video data.
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48.发明授权公开(公告)号：US11687798B2
公开(公告)日：2023-06-27
申请号：US16811823
申请日：2020-03-06
Applicant: Cisco Technology, Inc.
Inventor： Hugo Latapie , Enzo Fenoglio , Carlos M. Pignataro , Nagendra Kumar Nainar , David Delano Ward
Abstract: In one embodiment, a deep fusion reasoning engine receives network telemetry data collected from a network. The deep fusion reasoning engine learns resource utilizations for different heuristic packages that can be used in the network to evaluate operation of the network. The deep fusion reasoning engine selects one of the heuristic packages based on the resource utilizations learned for the different heuristic packages. The selected heuristic package comprises a subservice and a set of rules to be evaluated. The deep fusion reasoning engine deploys the selected heuristic package for execution by a device in the network to evaluate operation of the network using the set of rules.
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公开(公告)号：US20230179489A1
公开(公告)日：2023-06-08
申请号：US17545152
申请日：2021-12-08
Applicant: Cisco Technology, Inc.
Inventor： Hugo Latapie , Ozkan Kilic , Adam James Lawrence , Gaowen Liu , Andrew Albert Pletcher
Abstract: In one embodiment, a device provides information for display regarding an artificial intelligence metamodel that includes at least a symbolic layer and a sub-symbolic layer. The device receives an indication of a target node in a network to which the artificial intelligence metamodel is to be deployed. The device generates a modified version of the artificial intelligence metamodel based on resources available at the target node. The device deploys the modified version of the artificial intelligence metamodel for execution by the target node.
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公开(公告)号：US20230169962A1
公开(公告)日：2023-06-01
申请号：US17538148
申请日：2021-11-30
Applicant: Cisco Technology, Inc.
Inventor： Hugo Latapie , Ozkan Kilic , Adam James Lawrence , Gaowen Liu , Ramana Rao V. R. Kompella , Ali Payani
CPC classification number: G10L15/1815 , G10L15/063 , G10L25/48 , G10L15/24
Abstract: In one embodiment, a device identifies, using a semantic reasoning engine, activities in a location, based on sensor data obtained from a plurality of sensors deployed to the location. The device associates the activities with areas of the location in which they occurred. The device makes, using the semantic reasoning engine, an inference about a particular activity, based in part on where that activity occurred. The device raises, based on the inference, an alert regarding the particular activity.
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