Patents by Inventor Paul Hutkowski

Paul Hutkowski 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 method of character recognition using fully convolutional neural networks with attention
    Patent number: 11922318
    Abstract: Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.
    Type: Grant
    Filed: October 20, 2020
    Date of Patent: March 5, 2024
    Assignee: KODAK ALARIS, INC.
    Inventors: Felipe Petroski Such, Raymond Ptucha, Frank Brockler, Paul Hutkowski
  • System and method of character recognition using fully convolutional neural networks with attention
    Patent number: 11715014
    Abstract: Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.
    Type: Grant
    Filed: October 20, 2020
    Date of Patent: August 1, 2023
    Assignee: KODAK ALARIS INC.
    Inventors: Felipe Petroski Such, Raymond Ptucha, Frank Brockler, Paul Hutkowski
  • System and method of character recognition using fully convolutional neural networks
    Patent number: 10936862
    Abstract: Embodiments of the present disclosure include a method for extracting symbols from a digitized object. The method includes processing the word block against a dictionary. The method includes comparing the word block against a word in the dictionary, the comparison providing a confidence factor. The method includes outputting a prediction equal to the word when the confidence factor is greater than a predetermined threshold. The method includes evaluating properties of the word block when the confidence factor is less than the predetermined threshold. The method includes predicting a value of the word block based on the properties of the word block. The method further includes determining an error rate for the predicted value of the word block. The method includes outputting a value for the word block, the output equal to a calculated value corresponding to a value of the word block having the lowest error rate.
    Type: Grant
    Filed: September 19, 2017
    Date of Patent: March 2, 2021
    Assignee: Kodak Alaris Inc.
    Inventors: Felipe Petroski Such, Raymond Ptucha, Frank Brockler, Paul Hutkowski, Vatsala Singh
  • SYSTEM AND METHOD OF CHARACTER RECOGNITION USING FULLY CONVOLUTIONAL NEURAL NETWORKS WITH ATTENTION
    Publication number: 20210034850
    Abstract: Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.
    Type: Application
    Filed: October 20, 2020
    Publication date: February 4, 2021
    Applicant: Kodak Alaris Inc.
    Inventors: Felipe Petroski SUCH, Raymond PTUCHA, Frank BROCKLER, Paul HUTKOWSKI
  • SYSTEM AND METHOD OF CHARACTER RECOGNITION USING FULLY CONVOLUTIONAL NEURAL NETWORKS WITH ATTENTION
    Publication number: 20210034849
    Abstract: Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.
    Type: Application
    Filed: October 20, 2020
    Publication date: February 4, 2021
    Applicant: Kodak Alaris Inc.
    Inventors: Felipe Petroski SUCH, Raymond PTUCHA, Frank BROCKLER, Paul HUTKOWSKI
  • System and method of character recognition using fully convolutional neural networks with attention
    Patent number: 10846523
    Abstract: Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.
    Type: Grant
    Filed: November 14, 2017
    Date of Patent: November 24, 2020
    Assignee: KODAK ALARIS INC.
    Inventors: Felipe Petroski Such, Raymond Ptucha, Frank Brockler, Paul Hutkowski
  • SYSTEM AND METHOD OF CHARACTER RECOGNITION USING FULLY CONVOLUTIONAL NEURAL NETWORKS WITH ATTENTION
    Publication number: 20180137350
    Abstract: Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.
    Type: Application
    Filed: November 14, 2017
    Publication date: May 17, 2018
    Applicant: KODAK ALARIS INC.
    Inventors: Felipe Petroski SUCH, Raymond PTUCHA, Frank BROCKLER, Paul HUTKOWSKI
  • SYSTEM AND METHOD OF CHARACTER RECOGNITION USING FULLY CONVOLUTIONAL NEURAL NETWORKS
    Publication number: 20180137349
    Abstract: Embodiments of the present disclosure include a method for extracting symbols from a digitized object. The method includes processing the word block against a dictionary. The method includes comparing the word block against a word in the dictionary, the comparison providing a confidence factor. The method includes outputting a prediction equal to the word when the confidence factor is greater than a predetermined threshold. The method includes evaluating properties of the word block when the confidence factor is less than the predetermined threshold. The method includes predicting a value of the word block based on the properties of the word block. The method further includes determining an error rate for the predicted value of the word block. The method includes outputting a value for the word block, the output equal to a calculated value corresponding to a value of the word block having the lowest error rate.
    Type: Application
    Filed: September 19, 2017
    Publication date: May 17, 2018
    Applicant: Kodak Alaris Inc.
    Inventors: Felipe Petroski SUCH, Raymond Ptucha, Frank Brockler, Paul Hutkowski, Vatsala Singh