Patents by Inventor Shanshan Peng
Shanshan Peng 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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Patent number: 12203224Abstract: The present invention discloses an assembled bamboo sleeper, which is obtained by using a bamboo unit as a raw material, dried and modified at the temperature of 110-180° C., undergone coating treatment using a dopamine solution, adhesive dipping, curing and solidifying, assembling and gluing, further solidifying, further treatment using a dopamine solution, and anti-mildew and/or anti-corrosion and/or anti-insect treatment, and then fastened. The present invention further provides a preparation method for the foregoing bamboo sleeper. The bamboo sleeper prepared in the present invention is green and environmentally friendly, and applicable for ballasted tracks of railways and urban rail transit systems.Type: GrantFiled: April 18, 2019Date of Patent: January 21, 2025Assignee: HUNAN TAOHUAJIANG BAMBOO SCIENCE & TECHNOLOGY CO., LTD.Inventors: Jinbo Hu, Jian Peng, Weihong Zeng, Yanhui Xiong, Diqin Liu, Zhicheng Xue, Xianjun Li, Zhiping Wu, Shanshan Chang, Gonggang Liu, Ting Li
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Patent number: 12165424Abstract: Systems and/or techniques for facilitating image forgery detection via pixel-metadata consistency analysis are provided. In various embodiments, a system can receive an electronic image from a client device. In various cases, the system can obtain a pixel vector and/or an image metadata vector that correspond to the electronic image. In various aspects, the system can determine whether the electronic image is authentic or forged, based on analyzing the pixel vector and the image metadata vector via at least one machine learning model.Type: GrantFiled: July 13, 2021Date of Patent: December 10, 2024Assignee: PayPal, Inc.Inventors: Shanshan Peng, Jiazheng Zhang, Jiyi Zhang, Quan Jin Ferdinand Tang, Xiaodong Yu, Yuzhen Zhuo, Hong Qian, Zhe Chen, Runmin Wen
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Publication number: 20240311614Abstract: Systems and/or techniques for facilitating image forgery detection via headpose estimation may include a system that can receive a document from a client device. The system can identify, by executing a first trained machine learning model, an object that is depicted in the document. The system can determine, by executing a second trained machine learning model, a pose of the object. The system can determine, by executing a third trained machine learning model, whether the document is authentic or forged based on the pose of the object. The system can, in response to determining that the document is forged, transmit an unsuccessful validation message to the client device.Type: ApplicationFiled: March 19, 2024Publication date: September 19, 2024Inventors: Xiaodong Yu, Jiazheng Zhang, Jiyi Zhang, Quan Jin Ferdinand Tang, Shanshan Peng, Yuzhen Zhuo, Hong Qian, Runmin Wen
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Patent number: 12067475Abstract: Systems and/or techniques for facilitating image forgery detection via headpose estimation may include a system that can receive a document from a client device. The system can identify, by executing a first trained machine learning model, an object that is depicted in the document. The system can determine, by executing a second trained machine learning model, a pose of the object. The system can determine, by executing a third trained machine learning model, whether the document is authentic or forged based on the pose of the object. The system can, in response to determining that the document is forged, transmit an unsuccessful validation message to the client device.Type: GrantFiled: April 21, 2021Date of Patent: August 20, 2024Assignee: PayPal, Inc.Inventors: Xiaodong Yu, Jiazheng Zhang, Jiyi Zhang, Quan Jin Ferdinand Tang, Shanshan Peng, Yuzhen Zhuo, Hong Qian, Runmin Wen
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Publication number: 20240144728Abstract: Methods and systems are presented for signed document image analysis and fraud detection. An image of a document may be received from a user's device. A first layer of a machine learning engine is used to identify a signature and a name of the user within different areas of the received image. A second layer of the machine learning engine is used to extract a plurality of features from the different areas of the image. The plurality of features includes at least one visual feature representing the signature and at least one textual feature representing the name. A combined feature representation of the signature and the name is generated based on the plurality of features extracted from the image. A third layer of the machine learning engine is used to determine whether the signature of the user has been digitally altered, based on the combined feature representation.Type: ApplicationFiled: November 1, 2022Publication date: May 2, 2024Inventors: Quan Jin Ferdinand Tang, Jiyi Zhang, Jiazheng Zhang, Shanshan Peng, Jia Wen Lee
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Patent number: 11907658Abstract: Systems and methods for user-agent anomaly detection are disclosed. In one embodiment, a user-agent string may be embedded into a numerical data vector representation using a sentence embedding algorithm (e.g., FastText). A predictive score may be calculated based on the numerical data vector representation and using a probability distribution function model that models a likelihood of occurrence of the observed user-agent based on patterns learned from historic payload data (e.g., a Gaussian Mixture Model). The predictive score may be compared to a threshold and, based on the comparison, it may be determined whether the user-agent is fraudulent.Type: GrantFiled: May 5, 2021Date of Patent: February 20, 2024Assignee: PayPal, Inc.Inventors: Zhe Chen, Hewen Wang, Yuzhen Zhuo, Solomon kok how Teo, Shanshan Peng, Quan Jin Ferdinand Tang, Serafin Trujillo, Kenneth Bradley Snyder, Mandar Ganaba Gaonkar, Omkumar Mahalingam
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Patent number: 11893816Abstract: Methods and systems are presented for detecting a boundary of a document within a digital image. Upon receiving an image, the image is converted into a binary image. One or more kernel-based transformations are performed on the binary image using a horizontal kernel and a vertical kernel. A plurality of edges are identified based on the one or more kernel-based transformations. The plurality of edges includes a plurality of horizontal edges and a plurality of vertical edges. Multiple quadrilaterals are constructed using different combinations of horizontal edges and vertical edges from the plurality of edges. A particular quadrilateral is selected from the multiple quadrilaterals based on how well the edges fit the perimeters of the quadrilaterals. The selected quadrilateral is used to define a boundary of the document within the digital image.Type: GrantFiled: August 26, 2021Date of Patent: February 6, 2024Assignee: PayPal, Inc.Inventors: Shanshan Peng, Khine Phyo Yar, Yuzhen Zhuo
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Publication number: 20230061009Abstract: Methods and systems are presented for detecting a boundary of a document within a digital image. Upon receiving an image, the image is converted into a binary image. One or more kernel-based transformations are performed on the binary image using a horizontal kernel and a vertical kernel. A plurality of edges are identified based on the one or more kernel-based transformations. The plurality of edges includes a plurality of horizontal edges and a plurality of vertical edges. Multiple quadrilaterals are constructed using different combinations of horizontal edges and vertical edges from the plurality of edges. A particular quadrilateral is selected from the multiple quadrilaterals based on how well the edges fit the perimeters of the quadrilaterals. The selected quadrilateral is used to define a boundary of the document within the digital image.Type: ApplicationFiled: August 26, 2021Publication date: March 2, 2023Inventors: Shanshan Peng, Khine Phyo Yar, Yuzhen Zhuo
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Publication number: 20230005122Abstract: Systems and/or techniques for facilitating image forgery detection via pixel-metadata consistency analysis are provided. In various embodiments, a system can receive an electronic image from a client device. In various cases, the system can obtain a pixel vector and/or an image metadata vector that correspond to the electronic image. In various aspects, the system can determine whether the electronic image is authentic or forged, based on analyzing the pixel vector and the image metadata vector via at least one machine learning model.Type: ApplicationFiled: July 13, 2021Publication date: January 5, 2023Inventors: Shanshan Peng, Jiazheng Zhang, Jiyi Zhang, Quan Jin Ferdinand Tang, Xiaodong Yu, Yuzhen Zhuo, Hong Qian, Zhe Chen, Runmin Wen
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Publication number: 20220358289Abstract: Systems and methods for user-agent anomaly detection are disclosed. In one embodiment, a user-agent string may be embedded into a numerical data vector representation using a sentence embedding algorithm (e.g., FastText). A predictive score may be calculated based on the numerical data vector representation and using a probability distribution function model that models a likelihood of occurrence of the observed user-agent based on patterns learned from historic payload data (e.g., a Gaussian Mixture Model). The predictive score may be compared to a threshold and, based on the comparison, it may be determined whether the user-agent is fraudulent.Type: ApplicationFiled: May 5, 2021Publication date: November 10, 2022Inventors: Zhe Chen, Hewen Wang, Yuzhen Zhuo, Solomon kok how Teo, Shanshan Peng, Quan Jin Ferdinand Tang, Serafin Trujillo, Kenneth Bradley Snyder, Mandar Ganaba Gaonkar, Omkumar Mahalingam
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Publication number: 20220318597Abstract: Systems and/or techniques for facilitating image forgery detection via headpose estimation are provided. In various embodiments, a system can receive a document from a client device. In various cases, the system can identify, by executing a first trained machine learning model, an object that is depicted in the document. In various instances, the system can determine, by executing a second trained machine learning model, a pose of the object. In various aspects, the system can determine, by executing a third trained machine learning model, whether the document is authentic or forged based on the pose of the object. In various embodiments, the system can, in response to determining that the document is forged, transmit an unsuccessful validation message to the client device.Type: ApplicationFiled: April 21, 2021Publication date: October 6, 2022Inventors: Xiaodong Yu, Jiazheng Zhang, Jiyi Zhang, Quan Jin Ferdinand Tang, Shanshan Peng, Yuzhen Zhuo, Hong Qian, Runmin Wen