Patents by Inventor Daniel Llamocca Obregon

Daniel Llamocca Obregon 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).

  • System and methods for fast and scalable 2D convolutions and cross-correlations for processing image databases and videos on CPUs
    Patent number: 11954819
    Abstract: An optimal approach for computing convolutions and cross-correlations of large databases of images that can be arbitrarily large. Throughput is maximized by breaking each image into optimal blocks and then using overlap-and-add method to compute the final result. A parallelized 2D FFT is applied over each block that runs a thread for each physical core.
    Type: Grant
    Filed: February 26, 2021
    Date of Patent: April 9, 2024
    Assignee: UNM RAINFOREST INNOVATIONS
    Inventors: Marios Stephanou Pattichis, Cesar Carranza, Daniel Llamocca Obregon
  • System and methods for computing 2-D convolutions and cross-correlations
    Patent number: 11593907
    Abstract: Fast and scalable architectures and methods adaptable to available resources, that (1) compute 2-D convolutions using 1-D convolutions, (2) provide fast transposition and accumulation of results for computing fast cross-correlations or 2-D convolutions, and (3) provide parallel computations using pipelined 1-D convolvers. Additionally, fast and scalable architectures and methods that compute 2-D linear convolutions using Discrete Periodic Radon Transforms (DPRTs) including the use of scalable DPRT, Fast DPRT, and fast 1-D convolutions.
    Type: Grant
    Filed: September 30, 2020
    Date of Patent: February 28, 2023
    Inventors: Marios Stephanou Pattichis, Cesar Carranza, Daniel Llamocca Obregon
  • System and methods for the computation of the forward and inverse discrete periodic radon transform on GPUs and CPUs
    Patent number: 10943322
    Abstract: Fast and a scalable algorithms and methods adaptable to available resources for computing (1) the DPRT on multicore CPUs by distributing the computation of the DPRT primary directions among the different cores, and (2) the DPRT on GPUs using parallel, distributed, and synchronized ray computations among the GPU cores with “ray” referring to one of the sums required for computing the DPRT or its inverse along a prime direction.
    Type: Grant
    Filed: December 16, 2016
    Date of Patent: March 9, 2021
    Inventors: Marios Stephanou Pattichis, Cesar Carranza, Daniel Llamocca Obregon
  • SYSTEM AND METHODS FOR COMPUTING 2-D CONVOLUTIONS AND CROSS-CORRELATIONS
    Publication number: 20210065328
    Abstract: Fast and scalable architectures and methods adaptable to available resources, that (1) compute 2-D convolutions using 1-D convolutions, (2) provide fast transposition and accumulation of results for computing fast cross-correlations or 2-D convolutions, and (3) provide parallel computations using pipelined 1-D convolvers. Additionally, fast and scalable architectures and methods that compute 2-D linear convolutions using Discrete Periodic Radon Transforms (DPRTs) including the use of scalable DPRT, Fast DPRT, and fast 1-D convolutions.
    Type: Application
    Filed: September 30, 2020
    Publication date: March 4, 2021
    Inventors: Marios Stephanou PATTICHIS, Cesar CARRANZA, Daniel LLAMOCCA OBREGON
  • System and methods for computing 2-D convolutions and cross-correlations
    Patent number: 10810696
    Abstract: Fast and scalable architectures and methods adaptable to available resources, that (1) compute 2-D convolutions using 1-D convolutions, (2) provide fast transposition and accumulation of results for computing fast cross-correlations or 2-D convolutions, and (3) provide parallel computations using pipelined 1-D convolvers. Additionally, fast and scalable architectures and methods that compute 2-D linear convolutions using Discrete Periodic Radon Transforms (DPRTs) including the use of scalable DPRT, Fast DPRT, and fast 1-D convolutions.
    Type: Grant
    Filed: December 16, 2016
    Date of Patent: October 20, 2020
    Inventors: Marios Stephanou Pattichis, Cesar Carranza, Daniel Llamocca Obregon
  • SYSTEM AND METHODS FOR THE COMPUTATION OF THE FORWARD AND INVERSE DISCRETE PERIODIC RADON TRANSFORM ON GPUs AND CPUs
    Publication number: 20180357745
    Abstract: Fast and a scalable algorithms and methods adaptable to available resources for computing (1) the DPRT on multicore CPUs by distributing the computation of the DPRT primary directions among the different cores, and (2) the DPRT on GPUs using parallel, distributed, and synchronized ray computations among the GPU cores with “ray” referring to one of the sums required for computing the DPRT or its inverse along a prime direction.
    Type: Application
    Filed: December 16, 2016
    Publication date: December 13, 2018
    Inventors: Marios Stephanou PATTICHIS, Cesar CARRANZA, Daniel LLAMOCCA OBREGON
  • SYSTEM AND METHODS FOR COMPUTING 2-D CONVOLUTIONS AND CROSS-CORRELATIONS
    Publication number: 20180357744
    Abstract: Fast and scalable architectures and methods adaptable to available resources, that (1) compute 2-D convolutions using 1-D convolutions, (2) provide fast transposition and accumulation of results for computing fast cross-correlations or 2-D convolutions, and (3) provide parallel computations using pipelined 1-D convolvers. Additionally, fast and scalable architectures and methods that compute 2-D linear convolutions using Discrete Periodic Radon Transforms (DPRTs) including the use of scalable DPRT, Fast DPRT, and fast 1-D convolutions.
    Type: Application
    Filed: December 16, 2016
    Publication date: December 13, 2018
    Inventors: Marios Stephanou PATTICHIS, Cesar CARRANZA, Daniel LLAMOCCA OBREGON
  • System and methods for computing forward and inverse discrete periodic radon transform
    Patent number: 10049469
    Abstract: A fast and a scalable approach for computing the forward and inverse DPRT that uses: (i) a parallel array of fixed-point adder trees to compute the additions, (ii) circular shift registers to remove the need for accessing external memory components, (iii) an image block-based approach to DPRT computation that can fit the proposed architecture to available resources, and (iv) fast transpositions that are computed in one or a few clock cycles that do not depend on the size of the input image.
    Type: Grant
    Filed: December 15, 2014
    Date of Patent: August 14, 2018
    Assignee: STC.UNM
    Inventors: Cesar Carranza, Marios Stephanou Pattichis, Daniel Llamocca Obregon
  • SYSTEM AND METHODS FOR COMPUTING FORWARD AND INVERSE DISCRETE PERIODIC RADON TRANSFORM
    Publication number: 20160314603
    Abstract: A fast and a scalable approach for computing the forward and inverse DPRT that uses: (i) a parallel array of fixed-point adder trees to compute the additions, (ii) circular shift registers to remove the need for accessing external memory components, (iii) an image block-based approach to DPRT computation that can fit the proposed architecture to available resources, and (iv) fast transpositions that are computed in one or a few clock cycles that do not depend on the size of the input image.
    Type: Application
    Filed: December 15, 2014
    Publication date: October 27, 2016
    Inventors: Cesar Carranza, Marios Stephanou Pattichis, Daniel Llamocca Obregon