Patents by Inventor Rittika Adhikari
Rittika Adhikari has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20240020539Abstract: 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.Type: ApplicationFiled: July 19, 2023Publication date: January 18, 2024Inventors: Reza FARIVAR, Kenneth TAYLOR, Austin WALTERS, Joseph FORD, III, Rittika ADHIKARI
-
Patent number: 11710040Abstract: 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.Type: GrantFiled: July 2, 2021Date of Patent: July 25, 2023Assignee: Capital One Services, LLCInventors: Reza Farivar, Kenneth Taylor, Austin Walters, Joseph Ford, III, Rittika Adhikari
-
Patent number: 11386756Abstract: 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.Type: GrantFiled: July 28, 2020Date of Patent: July 12, 2022Assignee: Capital One Services, LLCInventors: Reza Farivar, Kenneth Taylor, Austin Walters, Joseph Ford, III, Rittika Adhikari
-
Publication number: 20210397898Abstract: 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.Type: ApplicationFiled: July 2, 2021Publication date: December 23, 2021Inventors: Reza FARIVAR, Kenneth TAYLOR, Austin WALTERS, Joseph FORD, III, Rittika ADHIKARI
-
Patent number: 11055573Abstract: 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.Type: GrantFiled: August 15, 2019Date of Patent: July 6, 2021Assignee: Capital One Services, LLCInventors: Reza Farivar, Kenneth Taylor, Austin Walters, Joseph Ford, III, Rittika Adhikari
-
Publication number: 20210195095Abstract: 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.Type: ApplicationFiled: March 8, 2021Publication date: June 24, 2021Applicant: Capital One Services, LLCInventors: Reza Farivar, Cody Stancil, Rittika Adhikari, Joseph Ford, III
-
Publication number: 20210092283Abstract: 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.Type: ApplicationFiled: September 19, 2019Publication date: March 25, 2021Applicant: Capital One Services, LLCInventors: Reza FARIVAR, Cody STANCIL, Rittika ADHIKARI, Joseph FORD, III
-
Patent number: 10944898Abstract: 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.Type: GrantFiled: September 19, 2019Date of Patent: March 9, 2021Assignee: Capital One Services, LLCInventors: Reza Farivar, Cody Stancil, Rittika Adhikari, Joseph Ford, III
-
Publication number: 20200357247Abstract: 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.Type: ApplicationFiled: July 28, 2020Publication date: November 12, 2020Inventors: Reza FARIVAR, Kenneth TAYLOR, Austin WALTERS, Joseph FORD, III, Rittika ADHIKARI
-
Patent number: 10769896Abstract: 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.Type: GrantFiled: May 1, 2019Date of Patent: September 8, 2020Assignee: Capital One Services, LLCInventors: Reza Farivar, Kenneth Taylor, Austin Walters, Joseph Ford, III, Rittika Adhikari
-
Publication number: 20200234083Abstract: 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.Type: ApplicationFiled: August 15, 2019Publication date: July 23, 2020Inventors: Reza Farivar, Kenneth Taylor, Austin Walters, Joseph Ford, III, Rittika Adhikari
-
Patent number: 10430692Abstract: 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.Type: GrantFiled: January 17, 2019Date of Patent: October 1, 2019Assignee: Capital One Services, LLCInventors: Reza Farivar, Kenneth Taylor, Austin Walters, Joseph Ford, III, Rittika Adhikari