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公开(公告)号：US20240203121A1
公开(公告)日：2024-06-20
申请号：US18084053
申请日：2022-12-19
IPC分类号： G06V20/40 , G06V10/22 , G06V10/764
CPC分类号： G06V20/41 , G06V10/235 , G06V10/764 , G06V20/46
摘要： An embodiment includes selecting, using a first attribute of a first object, the first object in a first volumetric video. The embodiment also includes selecting, using a second attribute of a second object, the second object in a second volumetric video, where the first attribute and the second attribute satisfy an aggregation rule. The embodiment also includes generating an aggregated volumetric video from the first volumetric video and the second volumetric video, where the generating of the aggregated video comprises rendering the first object and the second object simultaneously in the aggregated volumetric video based on the aggregation rule.
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公开(公告)号：US11874899B2
公开(公告)日：2024-01-16
申请号：US17122603
申请日：2020-12-15
IPC分类号： G06F18/214 , G06F18/21 , G06F18/22 , G06N3/08 , G06V20/40 , G06N3/045 , G06N3/047 , G06V10/82 , G06V20/70
CPC分类号： G06F18/214 , G06F18/2178 , G06F18/22 , G06N3/08 , G06V20/47
摘要： Using a first trained generative adversarial network, a first multimedia content is transformed into a text description of the first multimedia content. The text description is adjusted according to a constraint using a trained attention layer, the adjusting creating an adjusted text description. Using a trained model, the adjusted text description is transformed into a second multimedia content, the second multimedia content comprising an adjustment of the first multimedia content according to the constraint.
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公开(公告)号：US20230410439A1
公开(公告)日：2023-12-21
申请号：US17844352
申请日：2022-06-20
CPC分类号： G06T19/006 , G06N10/80 , G06V20/46 , G06V20/20 , G06T15/10
摘要： An embodiment includes accessing captured video of a first physical object in a physical environment. The embodiment also includes detecting a feature of the first physical object in a first frame of the video. The embodiment encodes a first qubit with a first quantum state based on a first value of the feature of the first physical object, and then entangles the first qubit with a second qubit forming an entangled qubit pair. The embodiment detects a second quantum state of the second qubit of the entangled qubit pair and renders computer-generated content of a virtual environment that includes a computer-generated first virtual object that corresponds to the first physical object, where the rendering comprises determining a property of the first virtual object based on the detected second quantum state.
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公开(公告)号：US12061952B2
公开(公告)日：2024-08-13
申请号：US17410553
申请日：2021-08-24
摘要： Using a model executing on a classical processor, a set of classical features is scored. The scored set of classical features is divided into a set of feature groups, a number of classical features in a group determined according to a qubit capability of a quantum processor. Using a model executing on the quantum processor and a group of the scored set of classical features, a set of quantum features is scored. The score of a quantum feature is adjusted according to an accuracy of the quantum data model. The scored set of classical features and the scored set of quantum features are combined according to a measure of differences between the scored set of classical features and the scored set of quantum features. Using the combined set of scored features and a first set of input data of a resource, a valuation of a resource is calculated.
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公开(公告)号：US20240171885A1
公开(公告)日：2024-05-23
申请号：US17990172
申请日：2022-11-18
IPC分类号： H04Q9/02
CPC分类号： H04Q9/02
摘要： By analyzing first configuration data of a set of sensors, a first configuration of the set of sensors is measured. A set of permutations of the first configuration is generated. For each permutation in the set of permutations, a corresponding set of virtual sensor data is generated. Using an analysis on each set of virtual sensor data and a set of real sensor data obtained using the first configuration, a corresponding analysis result is caused to be determined. Using the quality measure, a configuration producing a highest quality analysis result is determined. A contextual situation and the configuration are stored as a sensor configuration rule. By analyzing second configuration data of the set of sensors, a second configuration of the set of sensors is measured. The second configuration is adjusted according to the configuration specified in the sensor configuration rule.
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公开(公告)号：US11741370B2
公开(公告)日：2023-08-29
申请号：US16553823
申请日：2019-08-28
摘要： Methods, computer program products, and systems are presented. The methods include, for instance: generating a plurality of deep transfer learning networks including a source deep transfer learning network for a source domain and a target deep transfer learning network for a target domain. Transfer layers of the source deep transfer learning network are encoded to a chromosome, diversified, and integrated with the target deep transfer learning network and the target deep transfer learning network passing a predefined fitness threshold condition is produced.
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公开(公告)号：US20220188564A1
公开(公告)日：2022-06-16
申请号：US17122603
申请日：2020-12-15
摘要： Using a first trained generative adversarial network, a first multimedia content is transformed into a text description of the first multimedia content. The text description is adjusted according to a constraint using a trained attention layer, the adjusting creating an adjusted text description. Using a trained model, the adjusted text description is transformed into a second multimedia content, the second multimedia content comprising an adjustment of the first multimedia content according to the constraint.
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公开(公告)号：US20220101174A1
公开(公告)日：2022-03-31
申请号：US16948652
申请日：2020-09-28
IPC分类号： G06N20/00
摘要： An embodiment of the invention may include a method, computer program product, and computer system for managing a machine learning algorithm. The embodiment may include a computing device that distributes a first algorithm to a plurality of computing devices. The embodiment may include updates to the first algorithm, to create a second algorithm, by a first device of the plurality of computing devices. The first device is grouped with other devices in a first cluster of devices of the plurality of computing devices. The first cluster of computing devices comprises more than one computing device. Updating the first algorithm is performed based on information shared amongst the first cluster of devices.
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公开(公告)号：US11829886B2
公开(公告)日：2023-11-28
申请号：US15914222
申请日：2018-03-07
摘要： Simulating uncertainty in an artificial neural network is provided. Aleatoric uncertainty is simulated to measure what the artificial neural network does not understand from sensor data received from an object operating in a real-world environment by adding random values to edge weights between nodes in the artificial neural network during backpropagation of output data of the artificial neural network and measuring impact on the output data by the added random values to the edge weights between the nodes. Epistemic uncertainty is simulated to measure what the artificial neural network does not know by dropping out a selected node from each respective layer of the artificial neural network during forward propagation of the sensor data and measuring impact of dropped out nodes on the output data of the artificial neural network. An action corresponding to the object is performed based on the impact of simulating the aleatoric and epistemic uncertainty.
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公开(公告)号：US20230276196A1
公开(公告)日：2023-08-31
申请号：US17652772
申请日：2022-02-28
CPC分类号： H04W4/029 , G01S13/04 , G06K9/6262 , H04W4/025
摘要： A computer-implemented method, a computer system and a computer program product refine service inquiries through an understanding of user context. The method includes receiving a service inquiry from a user on a computing device. The method also includes capturing movement data within a user environment. The movement data is selected from a group consisting of audio data, video data and telemetry data extracted from a second device in the user environment. The method further includes determining a user context by correlating motion and position of the user with respect to the user environment. In addition, the method includes generating a set of predicted modifications to the service inquiry based on the user context. Lastly, the method includes displaying the set of predicted modifications to the service inquiry on the computing device.
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