Patents by Inventor Arunachalam Narayanaswamy
Arunachalam Narayanaswamy 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: 20230260126Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.Type: ApplicationFiled: April 24, 2023Publication date: August 17, 2023Inventors: Lily Hao Yi Peng, Dale R. Webster, Philip Charles Nelson, Varun Gulshan, Marc Adlai Coram, Martin Christian Stumpe, Derek Janme Wu, Arunachalam Narayanaswamy, Avinash Vaidyanathan Varadarajan, Katharine Blumer, Yun Liu, Ryan Poplin
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Patent number: 11636601Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.Type: GrantFiled: March 25, 2021Date of Patent: April 25, 2023Assignee: Google LLCInventors: Lily Hao Yi Peng, Dale R. Webster, Philip Charles Nelson, Varun Gulshan, Marc Adlai Coram, Martin Christian Stumpe, Derek Janme Wu, Arunachalam Narayanaswamy, Avinash Vaidyanathan Varadarajan, Katharine Blumer, Yun Liu, Ryan Poplin
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Publication number: 20230108319Abstract: Systems and methods for identifying visual features that influence a predictive model are provided. The technology employs an image translation function to introduce a visual feature into an image to create a modified image that can be fed to a predictive model. When the predictive model generates a different prediction for a given image than it does for a modified version of that image, the image translation function can then be used to make further modified versions that exaggerate the introduced visual feature. The technology thus aids in identifying visual features that influence the predictive model so that the model's conclusions can be understood, and so that those visual features can be further studied and tested.Type: ApplicationFiled: March 3, 2020Publication date: April 6, 2023Inventors: Arunachalam Narayanaswamy, Subhashini Venugopalan, Avinash Vaidyanathan Varadarajan
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Publication number: 20210209762Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.Type: ApplicationFiled: March 25, 2021Publication date: July 8, 2021Inventors: Lily Hao Yi Peng, Dale R. Webster, Philip Charles Nelson, Varun Gulshan, Marc Adlai Coram, Martin Christian Stumpe, Derek Janme Wu, Arunachalam Narayanaswamy, Avinash Vaidyanathan Varadarajan, Katharine Blumer, Yun Liu, Ryan Poplin
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Patent number: 10970841Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.Type: GrantFiled: August 18, 2017Date of Patent: April 6, 2021Assignee: Google LLCInventors: Lily Hao Yi Peng, Dale R. Webster, Philip Charles Nelson, Varun Gulshan, Marc Adlai Coram, Martin Christian Stumpe, Derek Janme Wu, Arunachalam Narayanaswamy, Avinash Vaidyanathan Varadarajan, Katharine Blumer, Yun Liu, Ryan Poplin
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Patent number: 10664708Abstract: Camera pose optimization, which includes determining the position and orientation of a camera in three-dimensional space at different times, is improved by detecting a higher-confidence reference object in the photographs captured by the camera and using the object to increase consistency and accuracy of pose data. Higher-confidence reference objects include objects that are stationary, fixed, easily recognized, and relatively large. In one embodiment, street level photographs of a geographic area are collected by a vehicle with a camera. The captured images are geo-coded using GPS data, which may be inaccurate. The vehicle drives in a loop and captures the same reference object multiple times from the substantially same position. The trajectory of the vehicle is then closed by aligning the points of multiple images where the trajectory crosses itself. This creates an additional constraint on the pose data, which in turn improves the data's consistency and accuracy.Type: GrantFiled: June 28, 2018Date of Patent: May 26, 2020Assignee: Google LLCInventors: Craig Lewin Robinson, Arunachalam Narayanaswamy, Marco Zennaro
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Publication number: 20190180441Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing fundus images using fundus image processing machine learning models. One of the methods includes obtaining a model input comprising one or more fundus images, each fundus image being an image of a fundus of an eye of a patient; processing the model input using a fundus image processing machine learning model, wherein the fundus image processing machine learning model is configured to process the model input comprising the one or more fundus image to generate a model output; and processing the model output to generate health analysis data.Type: ApplicationFiled: August 18, 2017Publication date: June 13, 2019Inventors: Lily Hao Yi Peng, Dale R. Webster, Philip Charles Nelson, Varun Gulshan, Marc Adlai Coram, Martin Christian Stumpe, Derek Janme Wu, Arunachalam Narayanaswamy, Avinash Vaidyanathan Varadarajan, Katharine Blumer, Yun Liu, Ryan Poplin
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Publication number: 20180373940Abstract: Camera pose optimization, which includes determining the position and orientation of a camera in three-dimensional space at different times, is improved by detecting a higher-confidence reference object in the photographs captured by the camera and using the object to increase consistency and accuracy of pose data. Higher-confidence reference objects include objects that are stationary, fixed, easily recognized, and relatively large. In one embodiment, street level photographs of a geographic area are collected by a vehicle with a camera. The captured images are geo-coded using GPS data, which may be inaccurate. The vehicle drives in a loop and captures the same reference object multiple times from the substantially same position. The trajectory of the vehicle is then closed by aligning the points of multiple images where the trajectory crosses itself. This creates an additional constraint on the pose data, which in turn improves the data's consistency and accuracy.Type: ApplicationFiled: June 28, 2018Publication date: December 27, 2018Inventors: Craig Lewin Robinson, Arunachalam Narayanaswamy, Marco Zennaro
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Patent number: 10037469Abstract: Camera pose optimization, which includes determining the position and orientation of a camera in three-dimensional space at different times, is improved by detecting a higher-confidence reference object in the photographs captured by the camera and using the object to increase consistency and accuracy of pose data. Higher-confidence reference objects include objects that are stationary, fixed, easily recognized, and relatively large. In one embodiment, street level photographs of a geographic area are collected by a vehicle with a camera. The captured images are geo-coded using GPS data, which may be inaccurate. The vehicle drives in a loop and captures the same reference object multiple times from the substantially same position. The trajectory of the vehicle is then closed by aligning the points of multiple images where the trajectory crosses itself. This creates an additional constraint on the pose data, which in turn improves the data's consistency and accuracy.Type: GrantFiled: December 9, 2014Date of Patent: July 31, 2018Assignee: Google LLCInventors: Craig Lewin Robinson, Arunachalam Narayanaswamy, Marco Zennaro
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Publication number: 20150161441Abstract: Camera pose optimization, which includes determining the position and orientation of a camera in three-dimensional space at different times, is improved by detecting a higher-confidence reference object in the photographs captured by the camera and using the object to increase consistency and accuracy of pose data. Higher-confidence reference objects include objects that are stationary, fixed, easily recognized, and relatively large. In one embodiment, street level photographs of a geographic area are collected by a vehicle with a camera. The captured images are geo-coded using GPS data, which may be inaccurate. The vehicle drives in a loop and captures the same reference object multiple times from the substantially same position. The trajectory of the vehicle is then closed by aligning the points of multiple images where the trajectory crosses itself. This creates an additional constraint on the pose data, which in turn improves the data's consistency and accuracy.Type: ApplicationFiled: December 9, 2014Publication date: June 11, 2015Inventors: Craig Lewin Robinson, Arunachalam Narayanaswamy, Marco Zennaro