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公开(公告)号：US11386756B2
公开(公告)日：2022-07-12
申请号：US16947308
申请日：2020-07-28
Applicant: Capital One Services, LLC
Inventor： Reza Farivar , Kenneth Taylor , Austin Walters , Joseph Ford, III , Rittika Adhikari
Abstract: An ATM device may receive a request to process an ATM transaction; dispense, via an instrument dispenser, a plurality of instruments based on the request; perform image segmentation of one or more images of an area surrounding the instrument dispenser, wherein the image segmentation is performed using a deep learning network trained using synthetic models of hands; detect, based on performing the image segmentation, that a user's hand approaches the instrument dispenser after dispensing the plurality of instruments; determine, after dispensing the plurality of instruments and after detecting that the user's hand approaches the instrument dispenser, that a portion of the plurality of instruments is present at the instrument dispenser; and perform one or more actions based on determining that the portion of the plurality of instruments is present at the instrument dispenser.
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公开(公告)号：US11710040B2
公开(公告)日：2023-07-25
申请号：US17305256
申请日：2021-07-02
Applicant: Capital One Services, LLC
Inventor： Reza Farivar , Kenneth Taylor , Austin Walters , Joseph Ford, III , Rittika Adhikari
IPC: G06N3/08 , G06F18/21 , G06F18/214 , G06V10/764 , G06V10/774 , G06V10/82 , G06V40/10
CPC classification number: G06N3/08 , G06F18/214 , G06F18/217 , G06V10/764 , G06V10/774 , G06V10/82 , G06V40/107
Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.
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公开(公告)号：US20220391583A1
公开(公告)日：2022-12-08
申请号：US17337792
申请日：2021-06-03
Applicant: Capital One Services, LLC
Inventor： Joseph Ford, III , Cody Stancil , Xiaowen Zhang
Abstract: Disclosed embodiments may include a method that may include receiving a corpus of unlabeled text documents, generating, using the first machine learning model, a first classification of each unlabeled text document in the corpus of unlabeled text documents as positive or negative, defining, using the first machine learning model and based on the first classification, a first subset of the unlabeled text documents and a second subset of the unlabeled text documents, generating, using the second machine learning model, a second classification of each unlabeled text document in the first subset of the unlabeled text documents as positive or negative, generating, using the third machine learning model, a third classification of each unlabeled text document in the second subset of the unlabeled text documents as positive or negative, and modifying the first classification, based on the second classification and the third classification, to create a fourth classification.
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公开(公告)号：US10430692B1
公开(公告)日：2019-10-01
申请号：US16250719
申请日：2019-01-17
Applicant: Capital One Services, LLC
Inventor： Reza Farivar , Kenneth Taylor , Austin Walters , Joseph Ford, III , Rittika Adhikari
Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.
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公开(公告)号：US12135936B2
公开(公告)日：2024-11-05
申请号：US17337792
申请日：2021-06-03
Applicant: Capital One Services, LLC
Inventor： Joseph Ford, III , Cody Stancil , Xiaowen Zhang
IPC: G06F40/20 , G06F18/214 , G06N20/20
Abstract: Disclosed embodiments may include a method that may include receiving a corpus of unlabeled text documents, generating, using the first machine learning model, a first classification of each unlabeled text document in the corpus of unlabeled text documents as positive or negative, defining, using the first machine learning model and based on the first classification, a first subset of the unlabeled text documents and a second subset of the unlabeled text documents, generating, using the second machine learning model, a second classification of each unlabeled text document in the first subset of the unlabeled text documents as positive or negative, generating, using the third machine learning model, a third classification of each unlabeled text document in the second subset of the unlabeled text documents as positive or negative, and modifying the first classification, based on the second classification and the third classification, to create a fourth classification.
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Patent Agency Ranking
公开(公告)号：US10944898B1
公开(公告)日：2021-03-09
申请号：US16576283
申请日：2019-09-19
Applicant: CAPITAL ONE SERVICES, LLC
Inventor： Reza Farivar , Cody Stancil , Rittika Adhikari , Joseph Ford, III
Abstract: A system for guiding image sensor angle settings in different environments. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include obtaining a plurality of synthetic images, the synthetic images representing a plurality of scenes; training a classification model to classify, based on the synthetic images, a plurality of images captured from an environment of a user by an image sensor; determining, based on the classification, whether the image sensor is positioned at a predetermined angle; and adjusting, based on the determination, a position of the image sensor.
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公开(公告)号：US11055573B2
公开(公告)日：2021-07-06
申请号：US16541406
申请日：2019-08-15
Applicant: Capital One Services, LLC
Inventor： Reza Farivar , Kenneth Taylor , Austin Walters , Joseph Ford, III , Rittika Adhikari
Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.
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公开(公告)号：US20210195095A1
公开(公告)日：2021-06-24
申请号：US17195293
申请日：2021-03-08
Applicant: Capital One Services, LLC
Inventor： Reza Farivar , Cody Stancil , Rittika Adhikari , Joseph Ford, III
Abstract: A system for guiding image sensor angle settings in different environments. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include obtaining a plurality of synthetic images, the synthetic images representing a plurality of scenes; training a classification model to classify, based on the synthetic images, a plurality of images captured from an environment of a user by an image sensor; determining, based on the classification, whether the image sensor is positioned at a predetermined angle; and adjusting, based on the determination, a position of the image sensor.
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公开(公告)号：US10769896B1
公开(公告)日：2020-09-08
申请号：US16400791
申请日：2019-05-01
Applicant: Capital One Services, LLC
Inventor： Reza Farivar , Kenneth Taylor , Austin Walters , Joseph Ford, III , Rittika Adhikari
Abstract: An ATM device may receive a request to process an ATM transaction; dispense, via an instrument dispenser, a plurality of instruments based on the request; perform image segmentation of one or more images of an area surrounding the instrument dispenser, wherein the image segmentation is performed using a deep learning network trained using synthetic models of hands; detect, based on performing the image segmentation, that a user's hand approaches the instrument dispenser after dispensing the plurality of instruments; determine, after dispensing the plurality of instruments and after detecting that the user's hand approaches the instrument dispenser, that a portion of the plurality of instruments is present at the instrument dispenser; and perform one or more actions based on determining that the portion of the plurality of instruments is present at the instrument dispenser.
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公开(公告)号：US20200234083A1
公开(公告)日：2020-07-23
申请号：US16541406
申请日：2019-08-15
Applicant: Capital One Services, LLC
Inventor： Reza Farivar , Kenneth Taylor , Austin Walters , Joseph Ford, III , Rittika Adhikari
Abstract: In some implementations, a training platform may receive data for generating synthetic models of a body part, such as a hand. The data may include information relating to a plurality of potential poses of the hand. The training platform may generate a set of synthetic models of the hand based on the information, where each synthetic model, in the set of synthetic models, representing a respective pose of the plurality of potential poses. The training platform may derive an additional set of synthetic models based on the set of synthetic models by performing one or more processing operations with respect to at least one synthetic model in the set of synthetic models, and causing the set of synthetic models and the additional set of synthetic models to be provided to a deep learning network to train the deep learning network to perform image segmentation, object recognition, or motion recognition.
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