Patents by Inventor Nilav Baran Ghosh

Nilav Baran Ghosh 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).

  • Patent number: 11830267
    Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive structural analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform digital document analysis using at least one of spatial fingerprint document image pair distance measures for document image pairs, object fingerprint document image pair distance measures for document image pairs, and semantic fingerprint document image pair distance measures for document image pairs.
    Type: Grant
    Filed: August 27, 2021
    Date of Patent: November 28, 2023
    Assignee: Optum, Inc.
    Inventors: Nilav Baran Ghosh, Indranil Basu, Piyal De
  • Patent number: 11682220
    Abstract: Solutions for more efficient and effective optical character recognition with respect to an input text segment are disclosed. In one example, a method includes processing an input text image using a deep character overlap detection machine learning model in order to generate a character map for the input text image, an overlap map for the input text image, and an affinity map for the input text image; generating an overlap-aware word boundary recognition output based at least in part on the character map, the overlap map, and the affinity map, wherein the overlap-aware word boundary recognition output describes one or more inferred word regions of the input text image; and performing one or more prediction-based actions based at least in part on the overlap-aware word boundary recognition output.
    Type: Grant
    Filed: March 15, 2021
    Date of Patent: June 20, 2023
    Assignee: OPTUM TECHNOLOGY, INC.
    Inventors: V Kishore Ayyadevara, Yerraguntla Yeshwanth Reddy, Snigdha Sree Borra, Nilav Baran Ghosh, Santosh Kumar Jami
  • Publication number: 20230066906
    Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive structural analysis. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform digital document analysis using at least one of spatial fingerprint document image pair distance measures for document image pairs, object fingerprint document image pair distance measures for document image pairs, and semantic fingerprint document image pair distance measures for document image pairs.
    Type: Application
    Filed: August 27, 2021
    Publication date: March 2, 2023
    Inventors: Nilav Baran Ghosh, Indranil Basu, Piyal De
  • Publication number: 20220300835
    Abstract: Solutions for more efficient and effective predictive code recommendation are disclosed. In one example, a method includes identifying a graph-based code recommendation machine learning model, wherein each inferred edge weight value of the graph-based code recommendation machine learning model is updated based at least in part on each compressed forward-adjusted temporal distance measure for an observed co-occurrence of any observed co-occurrences of a predictive code pair for the inferred edge weight value within one or more temporally-proximate occurrence subsets determined based at least in part on a plurality of training predictive code occurrences; processing the input predictive code using the graph-based code recommendation machine learning model to generate one or more related codes of the plurality of predictive codes for the input predictive code; and performing one or more prediction-based actions based at least in part on the one or more related codes.
    Type: Application
    Filed: March 18, 2021
    Publication date: September 22, 2022
    Inventors: Nilav Baran Ghosh, Abhilash Sivva, Srikanth B. Adibhatla
  • Publication number: 20220292294
    Abstract: Solutions for more efficient and effective optical character recognition with respect to an input text segment are disclosed. In one example, a method includes processing an input text image using a deep character overlap detection machine learning model in order to generate a character map for the input text image, an overlap map for the input text image, and an affinity map for the input text image; generating an overlap-aware word boundary recognition output based at least in part on the character map, the overlap map, and the affinity map, wherein the overlap-aware word boundary recognition output describes one or more inferred word regions of the input text image; and performing one or more prediction-based actions based at least in part on the overlap-aware word boundary recognition output.
    Type: Application
    Filed: March 15, 2021
    Publication date: September 15, 2022
    Inventors: V Kishore Ayyadevara, Yerraguntla Yeshwanth Reddy, Snigdha Sree Borra, Nilav Baran Ghosh, Santosh Kumar Jami
  • Patent number: 11227153
    Abstract: Systems and methods are configured to extract text from images (e.g., document images) utilizing a combination of optical character recognition processes and neural network-based analysis of various images to train a machine-learning object recognition model that is configured to identify text within images based on object-comparisons between known and unknown text within images. In certain embodiments, identified text within images may be utilized to identify corresponding regions-of-interest for extraction of image data encompassing a portion of an image that may be indexed based at least in part on text identified as corresponding to the particular region-of-interest.
    Type: Grant
    Filed: December 11, 2019
    Date of Patent: January 18, 2022
    Assignee: Optum Technology, Inc.
    Inventors: V Kishore Ayyadevara, Nilav Baran Ghosh, Yeshwanth Reddy, Vineet Shukla, Kartik Chaudhary
  • Publication number: 20210182547
    Abstract: Systems and methods are configured to extract text from images (e.g., document images) utilizing a combination of optical character recognition processes and neural network-based analysis of various images to train a machine-learning object recognition model that is configured to identify text within images based on object-comparisons between known and unknown text within images. In certain embodiments, identified text within images may be utilized to identify corresponding regions-of-interest for extraction of image data encompassing a portion of an image that may be indexed based at least in part on text identified as corresponding to the particular region-of-interest.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Kishore V. Ayyadevara, Nilav Baran Ghosh, Yeshwanth Reddy, Vineet Shukla, Kartik Chaudhary