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公开(公告)号：US20250094749A1
公开(公告)日：2025-03-20
申请号：US18969074
申请日：2024-12-04
Applicant: Maplebear Inc.
Inventor： Shiyuan Yang , Yilin Huang , Wentao Pan , Xiao Zhou
Abstract: A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.
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公开(公告)号：US20240202694A1
公开(公告)日：2024-06-20
申请号：US18169012
申请日：2023-02-14
Applicant: Maplebear Inc. (dba Instacart)
Inventor： Ganglu Wu , Shiyuan Yang , Xiao Zhou , Qi Wang , Qunwei Liu , Youming Luo
IPC: G06Q20/20 , G06K7/14 , G06Q30/0601 , G06T3/40 , G06V10/25
CPC classification number: G06Q20/208 , G06K7/1443 , G06Q30/0633 , G06Q30/0641 , G06T3/40 , G06V10/25
Abstract: An automated checkout system modifies received images of machine-readable labels to improve the performance of a label detection model that the system uses to decode item identifiers encoded in the machine-readable labels. For example, the automated checkout system may transform subregions of an image of a machine-readable label to adjust for distortions in the image's depiction of the machine-readable label. Similarly, the automated checkout system may identify readable regions within received images of machine-readable labels and apply a label detection model to those readable regions. By modifying received images of machine-readable labels, these techniques improve on existing computer-vision technologies by allowing for the effective decoding of machine-readable labels based on real-world images using relatively clean training data.
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公开(公告)号：US20240054449A1
公开(公告)日：2024-02-15
申请号：US17936232
申请日：2022-09-28
Applicant: Maplebear Inc. (dba Instacart)
Inventor： Lin Gao , Yilin Huang , Shiyuan Yang , Hao Wu , Ganglu Wu , Xiao Zhou
CPC classification number: G06Q10/087 , G06V20/52
Abstract: An online concierge system may use images received from shopping carts within retailers to determine the availability of items within those retailers. A shopping cart includes externally-facing cameras that automatically capture images of the area around the shopping cart as the shopping cart travels through a retailer. The online concierge system receives these images, which depict displays within the retailers from which a picker or a retailer patron can collect items. The online concierge system determines which items should be depicted in the images and which items are actually depicted in the images. The online concierge system identifies which items should be depicted, but are not depicted, and determines that these items are unavailable (e.g., out of stock) at that retailer. The online concierge system updates an availability database to indicate that these items are unavailable and may notify the retailer that the item is unavailable.
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公开(公告)号：US20250104040A1
公开(公告)日：2025-03-27
申请号：US18974543
申请日：2024-12-09
Applicant: Maplebear Inc.
Inventor： Yilin Huang , Ganglu Wu , Xiao Zhou , Youming Luo , Shiyuan Yang
Abstract: A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.
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公开(公告)号：US12050960B2
公开(公告)日：2024-07-30
申请号：US17703076
申请日：2022-03-24
Applicant: Maplebear Inc.
Inventor： Shiyuan Yang , Yilin Huang , Wentao Pan , Xiao Zhou
CPC classification number: G06K7/1413 , G06T7/10 , G06F2218/12 , G06T2207/20081
Abstract: A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.
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Patent Agency Ranking
公开(公告)号：US20240202475A1
公开(公告)日：2024-06-20
申请号：US18587719
申请日：2024-02-26
Applicant: Maplebear Inc.
Inventor： Ganglu Wu , Shiyuan Yang , Xiao Zhou , Qi Wang , Qunwei Liu , Youming Luo
IPC: G06K7/14 , G06Q30/0601 , G06T9/00 , G06V10/25
CPC classification number: G06K7/1413 , G06Q30/0633 , G06Q30/0641 , G06T9/00 , G06V10/25 , G06V2201/07
Abstract: An automated checkout system modifies received images of machine-readable labels to improve the performance of a label detection model that the system uses to decode item identifiers encoded in the machine-readable labels. For example, the automated checkout system may transform subregions of an image of a machine-readable label to adjust for distortions in the image's depiction of the machine-readable label. Similarly, the automated checkout system may identify readable regions within received images of machine-readable labels and apply a label detection model to those readable regions. By modifying received images of machine-readable labels, these techniques improve on existing computer-vision technologies by allowing for the effective decoding of machine-readable labels based on real-world images using relatively clean training data.
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公开(公告)号：US12205098B2
公开(公告)日：2025-01-21
申请号：US17874956
申请日：2022-07-27
Applicant: Maplebear Inc.
Inventor： Yilin Huang , Ganglu Wu , Xiao Zhou , Youming Luo , Shiyuan Yang
Abstract: A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.
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公开(公告)号：US12197998B2
公开(公告)日：2025-01-14
申请号：US18398739
申请日：2023-12-28
Applicant: Maplebear Inc.
Inventor： Shiyuan Yang , Yilin Huang , Wentao Pan , Xiao Zhou
Abstract: A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.
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公开(公告)号：US20240135123A1
公开(公告)日：2024-04-25
申请号：US18398739
申请日：2023-12-28
Applicant: Maplebear Inc.
Inventor： Shiyuan Yang , Yilin Huang , Wentao Pan , Xiao Zhou
CPC classification number: G06K7/1413 , G06T7/10 , G06F2218/12 , G06T2207/20081
Abstract: A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.
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公开(公告)号：US20240144688A1
公开(公告)日：2024-05-02
申请号：US18060473
申请日：2022-11-30
Applicant: Maplebear Inc. (dba Instacart)
Inventor： Lin Gao , Yilin Huang , Shiyuan Yang , Xiaofei Zhou , Xiao Zhou , Qunwei Liu
IPC: G06V20/52 , G06Q30/0601 , G06V10/74
CPC classification number: G06V20/52 , G06Q30/0633 , G06V10/761
Abstract: An automated checkout system accesses an image of an item inside a shopping cart and a location of the shopping cart within a store. The automated checkout system identifies a set of candidate items located within a threshold distance of the location of the shopping cart based on an item map. The item map describes a location of each item within the store and the location of each candidate item corresponds to a location of the candidate item on the item map. The automated checkout system inputs visual features of the item extracted from the image to a machine-learning model to identify the item by determining a similarity score between the item and each candidate item of the set of candidate items. After identifying the item, the automated checkout system displays a list comprising the item and additional items within the shopping cart to a user.
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