Patents by Inventor Yuxiao Hu
Yuxiao Hu 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: 11829848Abstract: A method includes obtaining training data for a classifier, the training data comprises one or more target classes, obtaining candidate background classes, selecting negative classes from the candidate background classes, wherein the negative classes exclude candidate background classes that are close to the target classes, wherein the negative classes exclude candidate background classes that are very different from the target classes, and wherein the negative classes include candidate background classes that are similar to the target classes, and training the classifier on a combined set of the selected negative classes and target classes.Type: GrantFiled: June 8, 2017Date of Patent: November 28, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Yuxiao Hu, Lei Zhang, Christopher J Buehler, Anna Roth, Cornelia Carapcea
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Patent number: 11751567Abstract: A steroidal piperidone derivative, a synthesis method, and a use thereof are provided. The steroidal piperidone derivative has a chemical structure shown in general formula (1) or general formula (2), where R is any one selected from the group consisting of alkyl, phenyl, substituted phenyl, and a heterocycle. In the synthesis method of the steroidal piperidone derivative, dehydroepiandrosterone (DHEA) is used as a basic raw material to prepare the steroidal piperidone derivative of the present disclosure through a series of reactions. A product prepared by the synthesis method has a high yield and is easily separated, and thus the synthesis method is the optimal method for preparing the steroidal piperidone derivative of the present disclosure. The present steroidal piperidone derivative exhibits prominent toxic activity against sucking pests, such as aphids, spider mites, rice planthoppers, and B. tabaci, and can be used for the control of a plant pest.Type: GrantFiled: September 23, 2022Date of Patent: September 12, 2023Inventors: Baojun Shi, Weiqi Jiang, Shichuang Ma, Yuxiao Hu, Qiangping Wang
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Publication number: 20230105315Abstract: A steroidal piperidone derivative, a synthesis method, and a use thereof are provided. The steroidal piperidone derivative has a chemical structure shown in general formula (1) or general formula (2), where R is any one selected from the group consisting of alkyl, phenyl, substituted phenyl, and a heterocycle. In the synthesis method of the steroidal piperidone derivative, dehydroepiandrosterone (DHEA) is used as a basic raw material to prepare the steroidal piperidone derivative of the present disclosure through a series of reactions. A product prepared by the synthesis method has a high yield and is easily separated, and thus the synthesis method is the optimal method for preparing the steroidal piperidone derivative of the present disclosure. The present steroidal piperidone derivative exhibits prominent toxic activity against sucking pests, such as aphids, spider mites, rice planthoppers, and B. tabaci, and can be used for the control of a plant pest.Type: ApplicationFiled: September 23, 2022Publication date: April 6, 2023Applicant: NORTHWEST A&F UNIVERSITYInventors: Baojun SHI, Weiqi JIANG, Shichuang MA, Yuxiao HU, Qiangping WANG
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Patent number: 10691981Abstract: Methods, systems, and computer programs are presented for training a deep neural network (DNN). One method includes an operation for training a predecessor network defined for image recognition of items, where parameters of a predecessor classifier are initialized with random numbers sampled from a predetermined distribution, and the predecessor classifier utilizes an image-classification probability function without bias. The method further includes an operation for training a successor network defined for image recognition of items in a plurality of classes, where parameters of a successor classifier are initialized with parameters learned from the predecessor network, and the successor classifier utilizes the image-classification probability function without bias. Further, the method includes operations for receiving an image for recognition, and recognizing the image utilizing the successor classifier.Type: GrantFiled: March 11, 2019Date of Patent: June 23, 2020Assignee: Microsoft Technology Licensing, LLCInventors: Yandong Guo, Yuxiao Hu, Christopher J Buehler, Cornelia Carapcea, Lei Zhang
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Publication number: 20190205705Abstract: Methods, systems, and computer programs are presented for training a deep neural network (DNN). One method includes an operation for training a predecessor network defined for image recognition of items, where parameters of a predecessor classifier are initialized with random numbers sampled from a predetermined distribution, and the predecessor classifier utilizes an image-classification probability function without bias. The method further includes an operation for training a successor network defined for image recognition of items in a plurality of classes, where parameters of a successor classifier are initialized with parameters learned from the predecessor network, and the successor classifier utilizes the image-classification probability function without bias. Further, the method includes operations for receiving an image for recognition, and recognizing the image utilizing the successor classifier.Type: ApplicationFiled: March 11, 2019Publication date: July 4, 2019Inventors: Yandong Guo, Yuxiao Hu, Christopher J. Buehler, Cornelia Carapcea, Lei Zhang
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Patent number: 10262240Abstract: Methods, systems, and computer programs are presented for training a deep neural network (DNN). One method includes an operation for training a predecessor network defined for image recognition of items, where parameters of a predecessor classifier are initialized with random numbers sampled from a predetermined distribution, and the predecessor classifier utilizes an image-classification probability function without bias. The method further includes an operation for training a successor network defined for image recognition of items in a plurality of classes, where parameters of a successor classifier are initialized with parameters learned from the predecessor network, and the successor classifier utilizes the image-classification probability function without bias. Further, the method includes operations for receiving an image for recognition, and recognizing the image utilizing the successor classifier.Type: GrantFiled: August 14, 2017Date of Patent: April 16, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Yandong Guo, Yuxiao Hu, Christopher J Buehler, Cornelia Carapcea, Lei Zhang
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Publication number: 20190050689Abstract: Methods, systems, and computer programs are presented for training a deep neural network (DNN). One method includes an operation for training a predecessor network defined for image recognition of items, where parameters of a predecessor classifier are initialized with random numbers sampled from a predetermined distribution, and the predecessor classifier utilizes an image-classification probability function without bias. The method further includes an operation for training a successor network defined for image recognition of items in a plurality of classes, where parameters of a successor classifier are initialized with parameters learned from the predecessor network, and the successor classifier utilizes the image-classification probability function without bias. Further, the method includes operations for receiving an image for recognition, and recognizing the image utilizing the successor classifier.Type: ApplicationFiled: August 14, 2017Publication date: February 14, 2019Inventors: Yandong Guo, Yuxiao Hu, Christopher J Buehler, Cornelia Carapcea, Lei Zhang
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Publication number: 20180330273Abstract: A method includes obtaining training data for a classifier, the training data comprises one or more target classes, obtaining candidate background classes, selecting negative classes from the candidate background classes, wherein the negative classes exclude candidate background classes that are close to the target classes, wherein the negative classes exclude candidate background classes that are very different from the target classes, and wherein the negative classes include candidate background classes that are similar to the target classes, and training the classifier on a combined set of the selected negative classes and target classes.Type: ApplicationFiled: June 8, 2017Publication date: November 15, 2018Inventors: YUXIAO HU, LEI ZHANG, Christopher J Buehler, ANNA ROTH, CORNELIA CARAPCEA
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Publication number: 20180330272Abstract: A method includes obtaining a first classifier trained on a first dataset having a first dataset class, the first classifier having a plurality of first parameters, obtaining a second dataset having a second dataset class, loading the first parameters into a second classifier, merging a subset of the first dataset class and the second dataset class into a merged class, and training the second classifier using the merged class.Type: ApplicationFiled: June 7, 2017Publication date: November 15, 2018Inventors: Yuxiao Hu, Lei Zhang, Christopher Buehler, Cha Zhang, Anna Roth, Cornelia Carapcea
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Patent number: 9953355Abstract: Identifying products in a physical store shopping environment. The method includes, using a first detection method, identifying that a given product likely belongs to a given set of products. The method further includes, using one or more other detection methods, determining that the product is likely a specific product from the given set of products.Type: GrantFiled: August 1, 2016Date of Patent: April 24, 2018Assignee: Microsoft Technology Licensing, LLCInventors: Jie Liu, Dimitrios Lymberopoulos, Mohammed Shoaib, Michel Goraczko, Nissanka Arachchige Bodhi Priyantha, Marcel Gavriliu, Suman Kumar Nath, Changhu Wang, Yuxiao Hu, Di Wang, Gerald Reuben DeJean, Lei Zhang
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Publication number: 20180033066Abstract: Identifying products in a physical store shopping environment. The method includes, using a first detection method, identifying that a given product likely belongs to a given set of products. The method further includes, using one or more other detection methods, determining that the product is likely a specific product from the given set of products.Type: ApplicationFiled: August 1, 2016Publication date: February 1, 2018Inventors: Jie Liu, Dimitrios Lymberopoulos, Mohammed Shoaib, Michel Goraczko, Nissanka Arachchige Bodhi Priyantha, Marcel Gavriliu, Suman Kumar Nath, Changhu Wang, Yuxiao Hu, Di Wang, Gerald Reuben DeJean, Lei Zhang
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Patent number: 8457358Abstract: Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.Type: GrantFiled: February 16, 2012Date of Patent: June 4, 2013Assignee: Microsoft CorporationInventors: Yuxiao Hu, Hong-Jiang Zhang, Mingjing Li, Lei Zhang
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Publication number: 20120139832Abstract: Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.Type: ApplicationFiled: February 16, 2012Publication date: June 7, 2012Applicant: Microsoft CorporationInventors: Yuxiao HU, Lei Zhang, Mingjing Li, Hong-Jiang Zhang
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Patent number: 8135183Abstract: Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.Type: GrantFiled: November 5, 2010Date of Patent: March 13, 2012Assignee: Microsoft CorporationInventors: Yuxiao Hu, Lei Zhang, Mingjing Li, Hong-Jiang Zhang
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Publication number: 20110050568Abstract: Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.Type: ApplicationFiled: November 5, 2010Publication date: March 3, 2011Applicant: Microsoft CorporationInventors: Yuxiao HU, Lei Zhang, Mingjing Li, Hong-Jiang Zhang
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Patent number: 7844086Abstract: Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.Type: GrantFiled: June 20, 2008Date of Patent: November 30, 2010Assignee: Microsoft CorporationInventors: Yuxiao Hu, Lei Zhang, Mingjing Li, Hong-Jiang Zhang
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Patent number: 7646909Abstract: A method and system for generating 3D images of faces from 2D images, for generating 2D images of the faces at different image conditions from the 3D images, and for recognizing a 2D image of a target face based on the generated 2D images is provided. The recognition system provides a 3D model of a face that includes a 3D image of a standard face under a standard image condition and parameters indicating variations of an individual face from the standard face. To generate the 3D image of a face, the recognition system inputs a 2D image of the face under a standard image condition. The recognition system then calculates parameters that map the points of the 2D image to the corresponding points of a 2D image of the standard face. The recognition system uses these parameters with the 3D model to generate 3D images of the face at different image conditions.Type: GrantFiled: August 19, 2008Date of Patent: January 12, 2010Assignee: Microsoft CorporationInventors: Dalong Jiang, Hong-Jiang Zhang, Lei Zhang, Shuicheng Yan, Yuxiao Hu
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Publication number: 20090052748Abstract: A method and system for generating 3D images of faces from 2D images, for generating 2D images of the faces at different image conditions from the 3D images, and for recognizing a 2D image of a target face based on the generated 2D images is provided. The recognition system provides a 3D model of a face that includes a 3D image of a standard face under a standard image condition and parameters indicating variations of an individual face from the standard face. To generate the 3D image of a face, the recognition system inputs a 2D image of the face under a standard image condition. The recognition system then calculates parameters that map the points of the 2D image to the corresponding points of a 2D image of the standard face. The recognition system uses these parameters with the 3D model to generate 3D images of the face at different image conditions.Type: ApplicationFiled: August 19, 2008Publication date: February 26, 2009Applicant: Microsoft CorporationInventors: Dalong Jiang, Hong-Jiang Zhang, Lei Zhang, Shuicheng Yan, Yuxiao Hu
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Publication number: 20080298637Abstract: Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.Type: ApplicationFiled: June 20, 2008Publication date: December 4, 2008Applicant: Microsoft CorporationInventors: Yuxiao Hu, Lei Zhang, Mingjing Li, Hong-Jiang Zhang
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Patent number: 7415152Abstract: A method and system for generating 3D images of faces from 2D images, for generating 2D images of the faces at different image conditions from the 3D images, and for recognizing a 2D image of a target face based on the generated 2D images is provided. The recognition system provides a 3D model of a face that includes a 3D image of a standard face under a standard image condition and parameters indicating variations of an individual face from the standard face. To generate the 3D image of a face, the recognition system inputs a 2D image of the face under a standard image condition. The recognition system then calculates parameters that map the points of the 2D image to the corresponding points of a 2D image of the standard face. The recognition system uses these parameters with the 3D model to generate 3D images of the face at different image conditions.Type: GrantFiled: April 29, 2005Date of Patent: August 19, 2008Assignee: Microsoft CorporationInventors: Dalong Jiang, Hong-Jiang Zhang, Lei Zhang, Shuicheng Yan, Yuxiao Hu