Patents by Inventor Shiyuan Yang
Shiyuan Yang 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: 20240144789Abstract: Disclosed are visual recognition and sensor fusion weight detection system and method. An example method includes: tracking, by a sensor system, objects and motions within a selected area of a store; activating, by the sensor system, a first computing device positioned in the selected area in response to detecting a presence of a customer within the selected area: identifying, by the sensor system, the customer and at least one item carried by the customer; transmitting, by the sensor system, identifying information of the customer and the at least one item to a computing server system via a communication network; measuring, by the first computing device, a weight of the at least one item; transmitting, by the first computing device, the weight to the computing server system via the communication network; and generating, by the computing server system, via the communication network, transaction information of the at least one item.Type: ApplicationFiled: January 10, 2024Publication date: May 2, 2024Inventors: Lin Gao, Shiyuan Yang
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Publication number: 20240144688Abstract: 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.Type: ApplicationFiled: November 30, 2022Publication date: May 2, 2024Inventors: Lin Gao, Yilin Huang, Shiyuan Yang, Xiaofei Zhou, Xiao Zhou, Qunwei Liu
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Publication number: 20240135123Abstract: 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.Type: ApplicationFiled: December 28, 2023Publication date: April 25, 2024Inventors: Shiyuan Yang, Yilin Huang, Wentao Pan, Xiao Zhou
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Publication number: 20240135353Abstract: Disclosed herein relates to a self-checkout anti-theft vehicle system, comprising: a self-checkout vehicle having a plurality of sensors and components implemented thereon, the self-checkout vehicle being used by shoppers for storing selected merchandises in a retail environment; and a centralized computing device. The centralized computing device is configured to: obtain information related to each merchandise selected and placed into the self-checkout vehicle by a shopper by exchanging data with the plurality of sensors and components via a first communication network, identify each merchandise via a second, different communication network based at least upon the information obtained from the plurality of sensors and components, and process payment information of each merchandise.Type: ApplicationFiled: January 3, 2024Publication date: April 25, 2024Inventors: Lin Gao, Yilin Huang, Shiyuan Yang, Ahmed Beshry
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Publication number: 20240138266Abstract: A method of making a thin film based structure. The method includes (a): forming an electrically conductive layer on a substrate such that the electrically conductive layer is releasably attached to the substrate. The method also includes (b): forming a ceramic or metallic thin film on the electrically conductive layer, on a side opposite the substrate. The electrically conductive layer and the substrate are arranged such that when an interface between them contacts a water-based liquid, the water-based liquid facilitates or causes release of the electrically conductive layer from the substrate, substantially without damaging the substrate.Type: ApplicationFiled: October 24, 2022Publication date: April 25, 2024Inventors: Zhengbao Yang, Shiyuan Liu
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Patent number: 11948044Abstract: 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.Type: GrantFiled: February 14, 2023Date of Patent: April 2, 2024Assignee: Maplebear Inc.Inventors: Ganglu Wu, Shiyuan Yang, Xiao Zhou, Qi Wang, Qunwei Liu, Youming Luo
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Patent number: 11915217Abstract: Disclosed herein relates to a self-checkout anti-theft vehicle system, comprising: a self-checkout vehicle having a plurality of sensors and components implemented thereon, the self-checkout vehicle being used by shoppers for storing selected merchandises in a retail environment; and a centralized computing device. The centralized computing device is configured to: obtain information related to each merchandise selected and placed into the self-checkout vehicle by a shopper by exchanging data with the plurality of sensors and components via a first communication network, identify each merchandise via a second, different communication network based at least upon the information obtained from the plurality of sensors and components, and process payment information of each merchandise.Type: GrantFiled: December 21, 2020Date of Patent: February 27, 2024Assignee: Maplebear Inc.Inventors: Lin Gao, Yilin Huang, Shiyuan Yang, Ahmed Beshry
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Patent number: 11908290Abstract: Disclosed are visual recognition and sensor fusion weight detection system and method. An example method includes: tracking, by a sensor system, objects and motions within a selected area of a store; activating, by the sensor system, a first computing device positioned in the selected area in response to detecting a presence of a customer within the selected area; identifying, by the sensor system, the customer and at least one item carried by the customer; transmitting, by the sensor system, identifying information of the customer and the at least one item to a computing server system via a communication network; measuring, by the first computing device, a weight of the at least one item; transmitting, by the first computing device, the weight to the computing server system via the communication network; and generating, by the computing server system, via the communication network, transaction information of the at least one item.Type: GrantFiled: May 18, 2021Date of Patent: February 20, 2024Assignee: Maplebear Inc.Inventors: Lin Gao, Shiyuan Yang
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Publication number: 20240054449Abstract: 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.Type: ApplicationFiled: September 28, 2022Publication date: February 15, 2024Inventors: Lin Gao, Yilin Huang, Shiyuan Yang, Hao Wu, Ganglu Wu, Xiao Zhou
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Publication number: 20240043057Abstract: Disclosed herein relates to a system, comprising: at least one load receiver mounted on a shopping cart or basket and configured to receive an item placed into the shopping cart or basket for a weighing operation; a plurality of sensors configured to detect a plurality of parameters relating to the weighing operation of the item including at least one of: a relative angle between a force sensing axis of the at least one load receiver and a direction of gravity, a motion of the shopping cart or basket, and an ambient temperature surrounding the shopping cart or basket and the at least one load receiver; and a processor configured to determine an actual weight of the item based on at least a portion of the plurality of parameters.Type: ApplicationFiled: October 18, 2023Publication date: February 8, 2024Inventors: Lin Gao, Michael Joseph Sanzari, Yilin Huang, Shiyuan Yang, Ahmed Beshry
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Publication number: 20240034381Abstract: An automated checkout system uses a shopping cart that is automatically charged when stacked into another shopping cart. Each shopping cart has a front charging connector and a rear charging connector. When a first shopping cart is stacked into a second shopping cart, the front charging connector of the first shopping cart connects with the rear charging connector of the second shopping cart. Electrical power can flow to the first shopping cart via the second shopping cart to charge a battery of the first shopping cart. The second shopping cart may be similarly stacked into a third shopping cart, wherein the second shopping cart receives electrical power from the third shopping cart. The second shopping cart may use this electrical power to charge its own battery or may provide some or all of the electrical power to the first shopping cart to charge the first shopping cart's battery.Type: ApplicationFiled: September 28, 2022Publication date: February 1, 2024Inventors: Lin Gao, Yilin Huang, Shiyuan Yang, Jianbo Meng, Yakun Li, Linhua Luo, Weiting Chen
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Publication number: 20240013184Abstract: 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.Type: ApplicationFiled: July 27, 2022Publication date: January 11, 2024Inventors: Yilin Huang, Ganglu Wu, Xiao Zhou, Youming Luo, Shiyuan Yang
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Publication number: 20240013185Abstract: 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.Type: ApplicationFiled: July 27, 2022Publication date: January 11, 2024Inventors: Lin Gao, Yilin Huang, Shiyuan Yang, Ganglu Wu, Yang Wang, Wentao Pan
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Publication number: 20240003707Abstract: A shopping cart's tracking system receives wheel motion data from a plurality of wheel sensors coupled to a plurality of wheels of the shopping cart, wherein the wheel motion data describes rotation of the plurality of wheels and orientation of the plurality of wheels. The tracking system predicts an estimated location of the shopping cart by applying a machine-learning location model to the wheel motion data. The machine-learning location model is trained with training examples that are generated by: receiving prior wheel motion data from the plurality of wheel sensors, partitioning the prior wheel motion data into a plurality of segments using a time window, receiving one or more baseline locations at one or more prior timestamps, and generating one or more training examples, each training example comprising a segment of prior wheel motion data and a baseline location with a timestamp overlapping the segment.Type: ApplicationFiled: July 26, 2022Publication date: January 4, 2024Inventors: Lin Gao, Yilin Huang, Shiyuan Yang, Xiaofei Zhou, Kaiyang Chu, Sikun Zhu
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Publication number: 20240001981Abstract: A shopping cart's tracking system determines a first baseline location of the shopping cart at a first timestamp with a wireless device located on the shopping cart detecting one or more external wireless devices (e.g., RFID tags) in the indoor environment. The shopping cart's tracking system receives wheel motion data from one or more wheel sensors coupled to one or more wheels of the shopping cart, wherein the wheel motion data describes rotation of the one or more wheels. The shopping cart's tracking system calculates a translation traveled by the shopping cart from the first baseline location based on the wheel motion data. The shopping cart's tracking system determines an estimated location of the shopping cart at a second timestamp based on the first baseline location and the translation. With the estimated location, the shopping cart can update a map with the estimated location of the shopping cart.Type: ApplicationFiled: July 26, 2022Publication date: January 4, 2024Inventors: Lin Gao, Yilin Huang, Shiyuan Yang, Xiaofei Zhou, Kaiyang Chu, Sikun Zhu
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Patent number: 11827263Abstract: Disclosed herein relates to a system, comprising: at least one load receiver mounted on a shopping cart or basket and configured to receive an item placed into the shopping cart or basket for a weighing operation; a plurality of sensors configured to detect a plurality of parameters relating to the weighing operation of the item including at least one of: a relative angle between a force sensing axis of the at least one load receiver and a direction of gravity, a motion of the shopping cart or basket, and an ambient temperature surrounding the shopping cart or basket and the at least one load receiver; and a processor configured to determine an actual weight of the item based on at least a portion of the plurality of parameters.Type: GrantFiled: August 24, 2022Date of Patent: November 28, 2023Assignee: Maplebear Inc.Inventors: Lin Gao, Michael Joseph Sanzari, Yilin Huang, Shiyuan Yang, Ahmed Beshry
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Publication number: 20230346982Abstract: The present disclosure provides a fluorescent contrast agent with a targeting function, and a preparation method and a use thereof, and belongs to the technical fields of nanomaterials and biomedical materials. The fluorescent contrast agent (MR780 NPs) of the present disclosure can specifically bind to CD206 on a surface of tumor-associated macrophages (TAMs). MR780 NPs accumulate in lymph nodes invaded by tumor cells and undergo an oxidation-reduction reaction with reduced glutathione in a tumor microenvironment, which triggers a fluorescence signal of MR780 NPs; and MR780 NPs do not accumulate and do not show fluorescence in normal lymph nodes. Therefore, the fluorescent contrast agent of the present disclosure can be used to diagnose lymph node metastasis (LNM) of breast cancer, realize the preoperative evaluation of LNM, assist in the clinical determination of tumor staging and the formulation of a surgical plan, and achieve the accurate resection under intraoperative fluorescence navigation.Type: ApplicationFiled: April 29, 2022Publication date: November 2, 2023Inventors: Shumin WANG, Xiaolong LIANG, Duo ZHAO, Shiyuan YANG, Menghong XU, Huiwen LI
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Publication number: 20230267292Abstract: 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.Type: ApplicationFiled: February 14, 2023Publication date: August 24, 2023Inventors: Ganglu Wu, Shiyuan Yang, Xiao Zhou, Qi Wang, Qunwei Liu, Youming Luo
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Publication number: 20230087587Abstract: Self-checkout vehicle systems and methods comprising a self-checkout vehicle having a camera(s), a weight sensor(s), and a processor configured to: (i) identify via computer vision a merchandise item selected by a shopper based on an identifier affixed to the selected item, and (ii) calculate a price of the merchandise item based on the identification and weight of the selected item. Computer vision systems and methods for identifying merchandise selected by a shopper comprising a processor configured to: (i) identify an identifier affixed to the selected merchandise and an item category of the selected merchandise, and (ii) compare the identifier and item category identified in each respective image to determine the most likely identification of the merchandise.Type: ApplicationFiled: September 22, 2022Publication date: March 23, 2023Inventors: Shiyuan YANG, Lin GAO, Yufeng HE, Xiao ZHOU, Yilin HUANG, Griffin KELLY, Isabel TSAI, Ahmed BESHRY
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Publication number: 20220410955Abstract: Disclosed herein relates to a system, comprising: at least one load receiver mounted on a shopping cart or basket and configured to receive an item placed into the shopping cart or basket for a weighing operation; a plurality of sensors configured to detect a plurality of parameters relating to the weighing operation of the item including at least one of: a relative angle between a force sensing axis of the at least one load receiver and a direction of gravity, a motion of the shopping cart or basket, and an ambient temperature surrounding the shopping cart or basket and the at least one load receiver; and a processor configured to determine an actual weight of the item based on at least a portion of the plurality of parameters.Type: ApplicationFiled: August 24, 2022Publication date: December 29, 2022Inventors: Lin Gao, Michael Joseph Sanzari, Yilin Huang, Shiyuan Yang, Ahmed Beshry