The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Oct. 01, 2024
Filed:
Apr. 04, 2022
National Technology & Engineering Solutions of Sandia, Llc, Albuquerque, NM (US);
Gabriel Carlisle Birch, Albuquerque, NM (US);
Brian John Redman, Albuquerque, NM (US);
Charles Fredrick LaCasse, IV, Albuquerque, NM (US);
Amber Lynn Dagel, Lafayette, CO (US);
Meghan Anne Sahakian, Albuquerque, NM (US);
Bryan James Kaehr, Albuquerque, NM (US);
Tu-Thach Quach, Albuquerque, NM (US);
Daniel Alvaro Calzada, Albuquerque, NM (US);
Bryana Lynn Woo, Albuquerque, NM (US);
Jaclynn Javonna Stubbs, Albuquerque, NM (US);
National Technology & Engineering Solutions of Sandia, LLC, Albuquerque, NM (US);
Abstract
A method and system architecture for designing a compressive sensing matrix for machine learning includes receiving an image associated with a classification task and; generating a sensing matrix. The sensing matrix includes an array of nonzero elements of the image. A prism array of prism elements is in communication with the sensing matrix. A row of values corresponding with an input angle of the prism array is mapped to a respective column corresponding with a detector. Then the detector detects light refracted at an output angle dictated by the physical shape of the prism element. A physical model of the detector is fabricated and generates a compressed representation of the image. A machine learning classification algorithm is applied to the compressed representation of the image and generates an optimized non-invertible final determination of the image.