Patents by Inventor Lars Oleson
Lars Oleson 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: 12346481Abstract: In an aspect, a system for image redaction is presented. The system includes an image recording device configured to generate image data. A computing device is in communication with the image recording device. The computing device is configured to detect a face in the image data as a function of a facial recognition process. The computing device is configured to modify the image data. Modifying the image data includes reversibly obscuring a face crop from a remaining portion of the image data. The computing device is configured to communicate the modified image data to another computing device.Type: GrantFiled: January 8, 2024Date of Patent: July 1, 2025Assignee: XailientInventors: Herman Yau, Lars Oleson, Andy Atkinson, Mallika Patel
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Patent number: 12045720Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.Type: GrantFiled: September 13, 2021Date of Patent: July 23, 2024Assignee: XAILIENTInventors: Lars Oleson, Shivanthan Yohanandan, Ryan Mccrea, Deepa Lakshmi Chandrasekharan, Sabina Pokhrel, Yousef Rabi, Zhenhua Zhang, Priyadharshini Devanand, Bernardo Rodeiro Croll, James J. Meyer
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Publication number: 20240233445Abstract: In one aspect, a system for implementing image privacy includes an image recording device configured to generate image data. The system include a computing device in communication with the image recording device. The computing device is configured to detect a face of the image data using a facial recognition process. The computing device is configured to receive user authorization of a data process of the face, wherein the user authorization is unique to an identity of the face. The computing device is configured to communicate data of the face to another computing device as a function of the user authorization.Type: ApplicationFiled: January 8, 2024Publication date: July 11, 2024Inventors: Herman Yau, Lars Oleson, Andy Atkinson, Mallika Patel
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Publication number: 20240232431Abstract: In an aspect, a system for image redaction is presented. The system includes an image recording device configured to generate image data. A computing device is in communication with the image recording device. The computing device is configured to detect a face in the image data as a function of a facial recognition process. The computing device is configured to modify the image data. Modifying the image data includes reversibly obscuring a face crop from a remaining portion of the image data. The computing device is configured to communicate the modified image data to another computing device.Type: ApplicationFiled: January 8, 2024Publication date: July 11, 2024Inventors: Herman Yau, Lars Oleson, Andy Atkinson, Mallika Patel
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Patent number: 11710240Abstract: Techniques for identifying pixel groups representing objects in an image include using images having multiple groups of pixels, grouped such that each pixel group represents a zone of interest and determining a pixel value for pixels within each pixel group based on a comparison of pixel values for each individual pixel within the group. A probability heat map is derived from the pixel group values using a first neural network using the pixel group values as input and produces the heat map having a set of graded values indicative of the probability that the respective pixel group includes an object of interest. A zone of interest is identified based on whether the groups of graded values meet a determined probability threshold objects of interest are identified within the at least one zone of interest by way of a second neural network.Type: GrantFiled: July 27, 2022Date of Patent: July 25, 2023Assignee: XailientInventors: Shivanthan Yohanandan, Lars Oleson
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Publication number: 20220366567Abstract: Techniques for identifying pixel groups representing objects in an image include using images having multiple groups of pixels, grouped such that each pixel group represents a zone of interest and determining a pixel value for pixels within each pixel group based on a comparison of pixel values for each individual pixel within the group. A probability heat map is derived from the pixel group values using a first neural network using the pixel group values as input and produces the heat map having a set of graded values indicative of the probability that the respective pixel group includes an object of interest. A zone of interest is identified based on whether the groups of graded values meet a determined probability threshold objects of interest are identified within the at least one zone of interest by way of a second neural network.Type: ApplicationFiled: July 27, 2022Publication date: November 17, 2022Inventors: Shivanthan Yohanandan, Lars Oleson
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Patent number: 11475572Abstract: Techniques for identifying pixel groups representing objects in an image include using images having multiple groups of pixels, grouped such that each pixel group represents a zone of interest and determining a pixel value for pixels within each pixel group based on a comparison of pixel values for each individual pixel within the group. A probability heat map is derived from the pixel group values using a first neural network using the pixel group values as input and produces the heat map having a set of graded values indicative of the probability that the respective pixel group includes an object of interest. A zone of interest is identified based on whether the groups of graded values meet a determined probability threshold objects of interest are identified within the at least one zone of interest by way of a second neural network.Type: GrantFiled: November 20, 2020Date of Patent: October 18, 2022Assignee: XailientInventors: Shivanthan Yohanandan, Lars Oleson
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Patent number: 11275970Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.Type: GrantFiled: May 7, 2021Date of Patent: March 15, 2022Assignee: XailientInventors: Lars Oleson, Shivanthan Yohanandan, Ryan Mccrea, Deepa Lakshmi Chandrasekharan, Sabina Pokhrel, Yousef Rabi, Zhenhua Zhang, Priyadharshini Devanand, Bernardo Rodeiro Croll, James J. Meyer
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Publication number: 20210406606Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.Type: ApplicationFiled: September 13, 2021Publication date: December 30, 2021Inventors: Lars Oleson, Shivanthan Yohanandan, Ryan Mccrea, Deepa Lakshmi Chandrasekharan, Sabina Pokhrel, Yousef Rabi, Zhenhua Zhang, Priyadharshini Devanand, Bernardo Rodeiro Croll, James J. Meyer
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Publication number: 20210406605Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.Type: ApplicationFiled: September 13, 2021Publication date: December 30, 2021Inventors: Lars Oleson, Shivanthan Yohanandan, Ryan Mccrea, Deepa Lakshmi Chandrasekharan, Sabina Pokhrel, Yousef Rabi, Zhenhua Zhang, Priyadharshini Devanand, Bernardo Rodeiro Croll, James J. Meyer
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Publication number: 20210406607Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.Type: ApplicationFiled: September 13, 2021Publication date: December 30, 2021Inventors: Lars Oleson, Shivanthan Yohanandan, Ryan Mccrea, Deepa Lakshmi Chandrasekharan, Sabina Pokhrel, Yousef Rabi, Zhenhua Zhang, Priyadharshini Devanand, Bernardo Rodeiro Croll, James J. Meyer
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Publication number: 20210350180Abstract: The invention provides systems and method for generating device-specific artificial neural network (ANN) models for distribution across user devices. Sample datasets are collected from devices in a particular environment or use case and include predictions by device-specific ANN models executing the user devices. The received datasets are used with existing datasets and stored ANN models to generate updated device-specific ANN models from each of the stored instances of the device ANN models based on the training data.Type: ApplicationFiled: May 7, 2021Publication date: November 11, 2021Inventors: Lars Oleson, Shivanthan Yohanandan, Ryan Mccrea, Deepa Lakshmi Chandrasekharan, Sabina Pokhrel, Yousef Rabi, Zhenhua Zhang, Priyadharshini Devanand, Bernardo Rodeiro Croll, James J. Meyer
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Publication number: 20210150721Abstract: Techniques for identifying pixel groups representing objects in an image include using images having multiple groups of pixels, grouped such that each pixel group represents a zone of interest and determining a pixel value for pixels within each pixel group based on a comparison of pixel values for each individual pixel within the group. A probability heat map is derived from the pixel group values using a first neural network using the pixel group values as input and produces the heat map having a set of graded values indicative of the probability that the respective pixel group includes an object of interest. A zone of interest is identified based on whether the groups of graded values meet a determined probability threshold objects of interest are identified within the at least one zone of interest by way of a second neural network.Type: ApplicationFiled: November 20, 2020Publication date: May 20, 2021Inventors: Shivanthan Yohanandan, Lars Oleson