Patents by Inventor Estelle Afshar
Estelle Afshar 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).
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Publication number: 20240144339Abstract: A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.Type: ApplicationFiled: January 5, 2024Publication date: May 2, 2024Inventors: Estelle Afshar, Matthew Hagen, Huiming Qu
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Patent number: 11954572Abstract: A method for machine learning-based classification may include training a machine learning model with a full training data set, the full training data set comprising a plurality of data points, to generate a first model state of the machine learning model, generating respective embeddings for the data points in the full training data set with the first model state of the machine learning model, applying a clustering algorithm to the respective embeddings to generate one or more clusters of the embeddings, identifying outlier embeddings from the one or more clusters of the embeddings, generating a reduced training data set comprising the full training data set less the data points associated with the outlier embeddings, training the machine learning model with the reduced training data set to a second model state, and applying the second model state to one or more data sets to classify the one or more data sets.Type: GrantFiled: May 16, 2023Date of Patent: April 9, 2024Assignee: Home Depot Product Authority, LLCInventors: Matthew Hagen, Estelle Afshar, Huiming Qu, Ala Eddine Ayadi, Jiaqi Wang
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Publication number: 20240070554Abstract: A method for machine learning-based classification may include training a machine learning model with a full training data set, the full training data set comprising a plurality of data points, to generate a first model state of the machine learning model, generating respective embeddings for the data points in the full training data set with the first model state of the machine learning model, applying a clustering algorithm to the respective embeddings to generate one or more clusters of the embeddings, identifying outlier embeddings from the one or more clusters of the embeddings, generating a reduced training data set comprising the full training data set less the data points associated with the outlier embeddings, training the machine learning model with the reduced training data set to a second model state, and applying the second model state to one or more data sets to classify the one or more data sets.Type: ApplicationFiled: May 16, 2023Publication date: February 29, 2024Inventors: Matthew Hagen, Estelle Afshar, Huiming Qu, Ala Eddine Ayadi, Jiaqi Wang
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Patent number: 11907987Abstract: A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.Type: GrantFiled: December 14, 2021Date of Patent: February 20, 2024Assignee: Home Depot Product Authority, LLCInventors: Estelle Afshar, Matthew Hagen, Huiming Qu
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Publication number: 20230298234Abstract: A method for editing a digital image includes receiving a user input indicative of a portion of an original digital image, determining an area of a surface comprising the portion by applying a plurality of different masks to the original image, receiving a user selection of a color to be applied to the original image to create a modified image, determining a modified brightness value for each pixel of the surface in the modified image according to original brightness values of corresponding pixels in the original image, and creating the modified image by applying the selected color to the surface according to the modified brightness values.Type: ApplicationFiled: February 3, 2022Publication date: September 21, 2023Inventors: Muhammad Osama Sakhi, Estelle Afshar, Yuanbo Wang
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Patent number: 11687841Abstract: A method for machine learning-based classification may include training a machine learning model with a full training data set, the full training data set comprising a plurality of data points, to generate a first model state of the machine learning model, generating respective embeddings for the data points in the full training data set with the first model state of the machine learning model, applying a clustering algorithm to the respective embeddings to generate one or more clusters of the embeddings, identifying outlier embeddings from the one or more clusters of the embeddings, generating a reduced training data set comprising the full training data set less the data points associated with the outlier embeddings, training the machine learning model with the reduced training data set to a second model state, and applying the second model state to one or more data sets to classify the one or more data sets.Type: GrantFiled: June 5, 2020Date of Patent: June 27, 2023Assignee: HOME DEPOT PRODUCT AUTHORITY, LLCInventors: Matthew Hagen, Estelle Afshar, Huiming Qu, Ala Eddine Ayadi, Jiaqi Wang
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Publication number: 20230057167Abstract: A method for displaying images similar to a selected image includes receiving, from a user, a selection of an anchor image, generating, using a machine learning model, an anchor embeddings set for the anchor image and respective candidate embeddings sets for a plurality of candidate images. The method also includes calculating a distance between the anchor embeddings set and each of the plurality of candidate embeddings sets and displaying at least one of the plurality of candidate images based on the calculated distance.Type: ApplicationFiled: August 17, 2022Publication date: February 23, 2023Inventors: Aron YU, Estelle AFSHAR
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Publication number: 20220253643Abstract: A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.Type: ApplicationFiled: December 14, 2021Publication date: August 11, 2022Inventors: Estelle Afshar, Matthew Hagen, Huiming Qu
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Publication number: 20220254144Abstract: A method includes retrieving, by a processor in an image classification system, a plurality of product images from a memory. A first image classifier is applied to a first of the plurality of product images. The first of the plurality of product images is associated with a first category. A second image classifier is applied to a second of the plurality of product images. The second of the plurality of product images is associated with a second category. A first result of the first image classifier for the first of the plurality of product images is stored in the memory. A second result of the second image classifier for the second of the plurality of product images is stored in the memory.Type: ApplicationFiled: February 3, 2022Publication date: August 11, 2022Inventors: Estelle Afshar, Tianlong Xu, Le Yu, Yuanbo Wang, James Morgan White
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Publication number: 20220230345Abstract: Systems and methods for providing measurement estimates for a building feature include receiving an image including the building feature. The method includes receiving, by a server, an image, the captured image including a building feature. The server locates a reference object in the image. The method includes segmenting the building feature to form a segmented image. A measurement of the building feature is estimated based on the segmented image and the reference object. The estimated measurement of the building feature is output by the server.Type: ApplicationFiled: January 19, 2021Publication date: July 21, 2022Inventors: Estelle Afshar, Yuanbo Wang, Stephanie Pertuit
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Patent number: 11200445Abstract: A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.Type: GrantFiled: January 22, 2020Date of Patent: December 14, 2021Assignee: Home Depot Product Authority, LLCInventors: Estelle Afshar, Matthew Hagen, Huiming Qu
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Publication number: 20210248662Abstract: This disclosure includes systems and methods for providing purchase recommendations to a user that may include items frequently purchased with a product selected by the user. The determination of which items are frequently purchased with which other items may account for both online and in-store transactions and may further account for both pairwise and multi-wise relationships. The recommendations may be provided on an electronic user interface, such as a website, in response to the user's selection of the product through the electronic user interface. The recommendations may be tailored to the user's selected product so that the recommended items are available in the same delivery channel as the user-selected product.Type: ApplicationFiled: April 26, 2021Publication date: August 12, 2021Inventors: Shubham Agarwal, Huiming Qu, Shawn Coombs, Estelle Afshar, Rini Devnath, Ramesh Gundeti, Prat Vemana, Kevin Hofmann
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Publication number: 20210224582Abstract: A computer-implemented method for determining image similarity includes determining, by a first neural network, a first feature value associated with a first characteristic of a first product based on an image of the first product. The method also includes determining, by a second neural network, a second feature value associated with a second characteristic of the first product based on the image of the first product. The method further involves calculating a first vector space distance between the first feature value and a third feature value associated with the first characteristic of a second product, and calculating a second vector space distance between the second feature value and a fourth feature value associated with the second characteristic of the second product. Additionally, the method includes determining a similarity value based on the first vector space distance and the second vector space distance.Type: ApplicationFiled: January 22, 2020Publication date: July 22, 2021Inventors: Estelle Afshar, Matthew Hagen, Huiming Qu
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Patent number: 10991026Abstract: This disclosure includes systems and methods for providing purchase recommendations to a user that may include items frequently purchased with a product selected by the user. The determination of which items are frequently purchased with which other items may account for both online and in-store transactions and may further account for both pairwise and multi-wise relationships. The recommendations may be provided on an electronic user interface, such as a website, in response to the user's selection of the product through the electronic user interface. The recommendations may be tailored to the user's selected product so that the recommended items are available in the same delivery channel as the user-selected product.Type: GrantFiled: August 10, 2016Date of Patent: April 27, 2021Assignee: Home Depot Product Authority, LLCInventors: Shubham Agarwal, Huiming Qu, Shawn Coombs, Estelle Afshar, Rini Devnath, Ramesh Gundeti, Prat Vemana, Kevin Hofmann
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Publication number: 20200387755Abstract: A method for machine learning-based classification may include training a machine learning model with a full training data set, the full training data set comprising a plurality of data points, to generate a first model state of the machine learning model, generating respective embeddings for the data points in the full training data set with the first model state of the machine learning model, applying a clustering algorithm to the respective embeddings to generate one or more clusters of the embeddings, identifying outlier embeddings from the one or more clusters of the embeddings, generating a reduced training data set comprising the full training data set less the data points associated with the outlier embeddings, training the machine learning model with the reduced training data set to a second model state, and applying the second model state to one or more data sets to classify the one or more data sets.Type: ApplicationFiled: June 5, 2020Publication date: December 10, 2020Inventors: Matthew Hagen, Estelle Afshar, Huiming Qu, Ala Eddine Ayadi, Jiaqi Wang
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Publication number: 20200104898Abstract: This disclosure includes systems and methods for providing accessory product recommendations to a user that may include items related to an anchor product selected by the user. The determination of accessory product recommendations may be made based on compatibility between anchor and accessory products, based on manually entered anchor-accessory product relationships, using an algorithm trained to determine anchor-accessory product relationships, or using other methods. The accessory recommendations may be provided along with the anchor product on an electronic user interface, such as a website, in response to the user's selection of the product through the electronic user interface. In this way, the accessory and anchor products may be viewed and/or selected by the user with a minimal number of clicks or user interactions through the electronic user interface.Type: ApplicationFiled: September 27, 2018Publication date: April 2, 2020Inventors: Xiquan Cui, Huiming Qu, Estelle Afshar, San-He Wu
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Publication number: 20180247363Abstract: A method of providing purchase recommendations to a user may include tracking user comparisons of products on an electronic commerce system, receiving a user selection of an anchor product from the products through an electronic user interface of the electronic commerce system, designating a recommended product from the products for recommendation to the user through the electronic commerce system according to a frequency with which the recommended product is compared with the anchor product based on the tracking, and presenting the designated recommended product to the user responsive to the user's selection of the anchor product.Type: ApplicationFiled: February 24, 2017Publication date: August 30, 2018Inventors: Shubham Agarwal, Huiming Qu, Shawn Coombs, Estelle Afshar, Rini Devnath, Prat Vemana, Xiquan Cui
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Publication number: 20180047083Abstract: This disclosure includes systems and methods for providing purchase recommendations to a user that may include items frequently purchased with a product selected by the user. The determination of which items are frequently purchased with which other items may account for both online and in-store transactions and may further account for both pairwise and multi-wise relationships. The recommendations may be provided on an electronic user interface, such as a website, in response to the user's selection of the product through the electronic user interface. The recommendations may be tailored to the user's selected product so that the recommended items are available in the same delivery channel as the user-selected product.Type: ApplicationFiled: August 10, 2016Publication date: February 15, 2018Inventors: Shubham Agarwal, Huiming Qu, Shawn Coombs, Estelle Afshar, Rini Devnath, Ramesh Gundeti, Prat Vemana, Kevin Hofmann