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公开(公告)号：US20200234179A1
公开(公告)日：2020-07-23
申请号：US16253366
申请日：2019-01-22
Applicant: United Technologies Corporation
Inventor： Kin Gwn Lore , Kishore K. Reddy
Abstract: According to an embodiment of the present disclosure, a method of training a machine learning model is provided. Input data is received from at least one remote device. A classifier is evaluated by determining a classification accuracy of the input data. A training data matrix of the input data is applied to a selected context autoencoder of a knowledge bank of autoencoders including at least one context autoencoder and the training data matrix is determined to be out of context for the selected autoencoder. The training data matrix is applied to each other context autoencoder of the at least one autoencoder and the training data matrix is determined to be out of context for each other context autoencoder. A new context autoencoder is constructed.
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公开(公告)号：US11544620B2
公开(公告)日：2023-01-03
申请号：US16253366
申请日：2019-01-22
Applicant: United Technologies Corporation
Inventor： Kin Gwn Lore , Kishore K. Reddy
Abstract: According to an embodiment of the present disclosure, a method of training a machine learning model is provided. Input data is received from at least one remote device. A classifier is evaluated by determining a classification accuracy of the input data. A training data matrix of the input data is applied to a selected context autoencoder of a knowledge bank of autoencoders including at least one context autoencoder and the training data matrix is determined to be out of context for the selected autoencoder. The training data matrix is applied to each other context autoencoder of the at least one autoencoder and the training data matrix is determined to be out of context for each other context autoencoder. A new context autoencoder is constructed.
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公开(公告)号：US10388005B2
公开(公告)日：2019-08-20
申请号：US15807359
申请日：2017-11-08
Applicant: UNITED TECHNOLOGIES CORPORATION
Inventor： Edgar A. Bernal , Kishore K. Reddy , Michael J. Giering , Ryan B. Noraas , Kin Gwn Lore
Abstract: A sensor system may comprise a sensor; a processor in electronic communication with the sensor; and/or a tangible, non-transitory memory configured to communicate with the processor, the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations. The operations may comprise recording, by the sensor, a low quality data sample; and/or applying, by the processor, a mapping function having a plurality of tuned parameters to the low quality data sample, producing a high quality data output.
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公开(公告)号：US20190050973A1
公开(公告)日：2019-02-14
申请号：US15807359
申请日：2017-11-08
Applicant: UNITED TECHNOLOGIES CORPORATION
Inventor： Edgar A. Bernal , Kishore K. Reddy , Michael J. Giering , Ryan B. Noraas , Kin Gwn Lore
CPC classification number: G06T5/20 , G06K9/6256 , G06T5/10 , G06T2207/20081 , H04N5/23229 , H04N7/181
Abstract: A sensor system may comprise a sensor; a processor in electronic communication with the sensor; and/or a tangible, non-transitory memory configured to communicate with the processor, the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations. The operations may comprise recording, by the sensor, a low quality data sample; and/or applying, by the processor, a mapping function having a plurality of tuned parameters to the low quality data sample, producing a high quality data output.
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