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公开(公告)号：US20190147288A1
公开(公告)日：2019-05-16
申请号：US15814009
申请日：2017-11-15
Applicant: Adobe Inc.
Inventor： Prakhar Gupta , Shubh Gupta , Ritwik Sinha , Sourav Pal , Ajaykrishnan Jayagopal
Abstract: A content saliency network is a machine-learned neural network that predicts the saliency of elements of a content item. The content saliency network may be used in a method that includes determining a set of elements in draft content and computing a first pixel-level vector for the content. The method may also include, for each element in the set of elements, computing a vector of simple features for the element, the simple features being computed from attributes of the element, computing a second pixel-level vector for the element, computing a third pixel-level vector for an intermediate context of the element, and providing the vectors to the content saliency network. The content saliency network provides a saliency score for the element. The method further includes generating an element-level saliency map of the content using the respective saliency scores for the set of elements and providing the saliency map to a requestor.
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Patent Agency Ranking
公开(公告)号：US11263470B2
公开(公告)日：2022-03-01
申请号：US15814009
申请日：2017-11-15
Applicant: Adobe Inc.
Inventor： Prakhar Gupta , Shubh Gupta , Ritwik Sinha , Sourav Pal , Ajaykrishnan Jayagopal
Abstract: A content saliency network is a machine-learned neural network that predicts the saliency of elements of a content item. The content saliency network may be used in a method that includes determining a set of elements in draft content and computing a first pixel-level vector for the content. The method may also include, for each element in the set of elements, computing a vector of simple features for the element, the simple features being computed from attributes of the element, computing a second pixel-level vector for the element, computing a third pixel-level vector for an intermediate context of the element, and providing the vectors to the content saliency network. The content saliency network provides a saliency score for the element. The method further includes generating an element-level saliency map of the content using the respective saliency scores for the set of elements and providing the saliency map to a requestor.
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13.发明申请公开(公告)号：US20200334545A1
公开(公告)日：2020-10-22
申请号：US16389628
申请日：2019-04-19
Applicant: Adobe Inc.
Inventor： Atanu Sinha , Prakhar Gupta , Manoj Kilaru , Madhav Goel , Deepanshu Bansal , Deepali Jain , Aniket Raj
IPC: G06N5/02 , G06F16/2457 , G06N5/04 , G06Q30/02 , G06F16/901 , G06N3/04
Abstract: A method includes accessing a subject entity and a subject relation of a focal platform and accessing a knowledge graph representative of control performance data. Further, the method includes computing a set of ranked target entities that cause the subject entity based on the subject relation or are an effect of the subject entity based on the subject relation. Computing the set of ranked target entities is performed using relational hops from the subject entity within the knowledge graph performed using the subject relation and reward functions. The method also includes transmitting the set of ranked target entities to the focal platform. The set of ranked target entities is usable for modifying a user interface of an interactive computing environment provided by the focal platform.
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公开(公告)号：US20200097495A1
公开(公告)日：2020-03-26
申请号：US16698383
申请日：2019-11-27
Applicant: Adobe Inc.
Inventor： Prakhar Gupta , Iftikhar Ahamath Burhanuddin , Harvineet Singh , Atanu Ranjan Sinha
IPC: G06F16/33 , G06F16/242 , G06F16/332 , G10L15/22 , H04L12/58
Abstract: This disclosure covers methods, non-transitory computer readable media, and systems that use an intelligent analytics interface to process natural-language and other inputs to configure an analytics task for the system. The disclosed methods, non-transitory computer readable media, and systems provide the intelligent analytics interface to facilitate an exchange between the systems and a user to determine values for the analytics task. The methods, non-transitory computer readable media, and systems then use these values to execute an analytics task.
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公开(公告)号：US20190251707A1
公开(公告)日：2019-08-15
申请号：US15897807
申请日：2018-02-15
Applicant: Adobe Inc.
Inventor： Prakhar Gupta , Sourav Pal , Shubh Gupta , Ritwik Sinha , Ajaykrishnan Jayagopal
Abstract: A content saliency network is a machine-learned neural network that predicts the saliency of elements of a content item. The content saliency network may be used in a method that includes determining a set of elements in a UI and computing a first context vector for the content. The method may also include, for each element in the set of elements, computing a vector of simple features for the element, the simple features being computed from attributes of the element, computing a second context vector for the element, computing a third context vector for an intermediate context of the element, and providing the vectors to the content saliency network. The content saliency network provides a saliency score for the element. The method further includes generating an element-level saliency map of the content using the respective saliency scores for the set of elements and providing the saliency map to a requestor.
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公开(公告)号：US10380155B2
公开(公告)日：2019-08-13
申请号：US15163531
申请日：2016-05-24
Applicant: Adobe Inc.
Inventor： Kokil Jaidka , Prakhar Gupta , Harvineet Singh , Iftikhar Ahamath Burhanuddin
Abstract: Natural language notification generation techniques and system are described. In an implementation, natural language notifications are generated to provide insight into alerts related to a metric, underlying causes of the alert from other metrics, and relationships of the metric to other metrics. In this way, a user may gain this insight in an efficient, intuitive, and time effective manner.
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