Patents by Inventor Steven A. Israel
Steven A. Israel 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: 11587323Abstract: A machine accesses a set of image target models, each image target model being associated with model parameters, the model parameters comprising at least an operational domain, an expected input image quality, and an expected orientation. The machine receives an image for processing by one or more image target models from the set, the image including metadata specifying image parameters of the received image. The machine identifies, based on the image parameters in the metadata of the received image and the model parameters of one or more models in the set, a first subset of the set of image target models including image target models that are capable of processing the received image. The machine provides the received image to at least one image target model in the first subset.Type: GrantFiled: May 14, 2020Date of Patent: February 21, 2023Assignee: Raytheon CompanyInventor: Steven A. Israel
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Patent number: 11468266Abstract: A machine receives a large image having large image dimensions that exceed memory threshold dimensions. The large image includes metadata. The machine adjusts an orientation and a scaling of the large image based on the metadata. The machine divides the large image into a plurality of image tiles, each image tile having tile dimensions smaller than or equal to the memory threshold dimensions. The machine provides the plurality of image tiles to an artificial neural network. The machine identifies, using the artificial neural network, at least a portion of the target in at least one image tile. The machine identifies the target in the large image based on at least the portion of the target being identified in at least one image tile.Type: GrantFiled: September 27, 2019Date of Patent: October 11, 2022Assignee: Raytheon CompanyInventors: Jonathan Goldstein, Stephen J. Raif, Philip A. Sallee, Jeffrey S. Klein, Steven A. Israel, Franklin Tanner, Shane A. Zabel, James Talamonti, Lisa A. Mccoy
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Patent number: 11080837Abstract: Discussed herein are architectures and techniques for improving execution or training of machine learning techniques. A method can include receiving a request for image data, the request indicating an analysis task to be performed using the requested image data, determining a minimum image quality score for performing the analysis task, issuing a request for image data associated with an image quality at last equal to, or greater than, the determined minimum image quality score, receiving, in response to the request, image data with an image quality score greater than, or equal to, the determined minimum image quality score, and providing the received image data to (a) a machine learning (ML) model executor to perform the image analysis task or (b) an ML model trainer that trains the ML model to perform the image analysis task.Type: GrantFiled: July 9, 2019Date of Patent: August 3, 2021Assignee: Raytheon CompanyInventor: Steven A. Israel
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Publication number: 20210097344Abstract: A machine receives a large image having large image dimensions that exceed memory threshold dimensions. The large image includes metadata. The machine adjusts an orientation and a scaling of the large image based on the metadata. The machine divides the large image into a plurality of image tiles, each image tile having tile dimensions smaller than or equal to the memory threshold dimensions. The machine provides the plurality of image tiles to an artificial neural network. The machine identifies, using the artificial neural network, at least a portion of the target in at least one image tile. The machine identifies the target in the large image based on at least the portion of the target being identified in at least one image tile.Type: ApplicationFiled: September 27, 2019Publication date: April 1, 2021Inventors: Jonathan Goldstein, Stephen J. Raif, Philip A. Sallee, Jeffrey S. Klein, Steven A. Israel, Franklin Tanner, Shane A. Zabel, James Talamonti, Lisa A. Mccoy
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Publication number: 20210012477Abstract: Discussed herein are architectures and techniques for improving execution or training of machine learning techniques. A method can include receiving a request for image data, the request indicating an analysis task to be performed using the requested image data, determining a minimum image quality score for performing the analysis task, issuing a request for image data associated with an image quality at last equal to, or greater than, the determined minimum image quality score, receiving, in response to the request, image data with an image quality score greater than, or equal to, the determined minimum image quality score, and providing the received image data to (a) a machine learning (ML) model executor to perform the image analysis task or (b) an ML model trainer that trains the ML model to perform the image analysis task.Type: ApplicationFiled: July 9, 2019Publication date: January 14, 2021Inventor: Steven A. Israel
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Publication number: 20200410245Abstract: A machine accesses a set of image target models, each image target model being associated with model parameters, the model parameters comprising at least an operational domain, an expected input image quality, and an expected orientation. The machine receives an image for processing by one or more image target models from the set, the image including metadata specifying image parameters of the received image. The machine identifies, based on the image parameters in the metadata of the received image and the model parameters of one or more models in the set, a first subset of the set of image target models including image target models that are capable of processing the received image. The machine provides the received image to at least one image target model in the first subset.Type: ApplicationFiled: May 14, 2020Publication date: December 31, 2020Inventor: Steven A. Israel
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Patent number: 6993378Abstract: Methods involving extraction of information from the inherent variability of physiometrics, including data on cardiovascular and pulmonary functions such as heart rate variability, characteristics of ECG traces, pulse, oxygenation of subcutaneous blood, respiration rate, temperature or CO2 content of exhaled air, heart sounds, and body resonance, can be used to identify individual subjects, particularly humans. Biometric data for use in the methods can be obtained either from contact sensors or at a distance. The methods can be performed alone or can be fused with previous identification algorithms.Type: GrantFiled: June 25, 2002Date of Patent: January 31, 2006Assignee: Science Applications International CorporationInventors: Mark D. Wiederhold, Steven A. Israel, Rodney P. Meyer, John M. Irvine
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Publication number: 20030135097Abstract: Methods involving extraction of information from the inherent variability of physiometrics, including data on cardiovascular and pulmonary functions such as heart rate variability, characteristics of ECG traces, pulse, oxygenation of subcutaneous blood, respiration rate, temperature or CO2 content of exhaled air, heart sounds, and body resonance, can be used to identify individual subjects, particularly humans. Biometric data for use in the methods can be obtained either from contact sensors or at a distance. The methods can be performed alone or can be fused with previous identification algorithms.Type: ApplicationFiled: June 25, 2002Publication date: July 17, 2003Applicant: Science Applications International CorporationInventors: Mark D. Wiederhold, Steven A. Israel, Rodney P. Meyer, John M. Irvine