Patents by Inventor Ravil KASHYAP

Ravil KASHYAP 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).

  • Publication number: 20250036690
    Abstract: Systems and methods are disclosed for automatically extracting keys and corresponding values in any type of source document. Extracting desired words from the tokens in any type of document is based on a uniform approach to represent the source document. This uniform representation encodes features of the desired tokens along with the neighborhood information so that values associated with a given key can be extracted. The disclosed technique learns the representation of tokens independent of source document type and the learned representation is then used to determine relationships between multiple tokens. The neighborhood information and position information are used to determine various relationships between keys and values.
    Type: Application
    Filed: July 28, 2023
    Publication date: January 30, 2025
    Inventors: Badri Nath, Vijayendra Mysore Shamanna, Yashu Seth, Ravil Kashyap, Kaushal Kishore Hebbar, Henry Thomas Peter, Simha Sadasiva
  • Publication number: 20240013563
    Abstract: The present disclosure relates to a system and method to extract information from unstructured image documents. The extraction technique is content-driven and not dependent on the layout of a particular image document type. The disclosed method breaks down an image document into smaller images using the text cluster detection algorithm. The smaller images are converted into text samples using optical character recognition (OCR). Each of the text samples is fed to a trained machine learning model. The model classifies each text sample into one of a plurality of pre-determined field types. The desired value extraction problem may be converted into a question-answering problem using a pre-trained model. A fixed question is formed on the basis of the classified field type. The output of the question-answering model may be passed through a rule-based post-processing step to obtain the final answer.
    Type: Application
    Filed: September 25, 2023
    Publication date: January 11, 2024
    Inventors: Yashu SETH, Shaik Kamran MOINUDDIN, Ravil KASHYAP, Vijayendra Mysore SHAMANNA, Henry Thomas Peter, Simha SADASIVA
  • Patent number: 11769341
    Abstract: The present disclosure relates to a system and method to extract information from unstructured image documents. The extraction technique is content-driven and not dependent on the layout of a particular image document type. The disclosed method breaks down an image document into smaller images using the text cluster detection algorithm. The smaller images are converted into text samples using optical character recognition (OCR). Each of the text samples is fed to a trained machine learning model. The model classifies each text sample into one of a plurality of pre-determined field types. The desired value extraction problem may be converted into a question-answering problem using a pre-trained model. A fixed question is formed on the basis of the classified field type. The output of the question-answering model may be passed through a rule-based post-processing step to obtain the final answer.
    Type: Grant
    Filed: August 18, 2021
    Date of Patent: September 26, 2023
    Assignee: Ushur, Inc.
    Inventors: Yashu Seth, Ravil Kashyap, Shaik Kamran Moinuddin, Vijayendra Mysore Shamanna, Henry Thomas Peter, Simha Sadasiva
  • Publication number: 20220058383
    Abstract: The present disclosure relates to a system and method to extract information from unstructured image documents. The extraction technique is content-driven and not dependent on the layout of a particular image document type. The disclosed method breaks down an image document into smaller images using the text cluster detection algorithm. The smaller images are converted into text samples using optical character recognition (OCR). Each of the text samples is fed to a trained machine learning model. The model classifies each text sample into one of a plurality of pre-determined field types. The desired value extraction problem may be converted into a question-answering problem using a pre-trained model. A fixed question is formed on the basis of the classified field type. The output of the question-answering model may be passed through a rule-based post-processing step to obtain the final answer.
    Type: Application
    Filed: August 18, 2021
    Publication date: February 24, 2022
    Inventors: Yashu SETH, Ravil KASHYAP, Shaik Kamran MOINUDDIN, Vijayendra Mysore SHAMANNA, Henry Thomas PETER, Simha SADASIVA