Patents by Inventor Venkata Satya Pradeep Karuturi

Venkata Satya Pradeep Karuturi 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).

  • MULTIMODAL SENTIMENT CLASSIFICATION
    Publication number: 20230418910
    Abstract: Sentiment classification can be implemented by an entity-level multimodal sentiment classification neural network. The neural network can include left, right, and target entity subnetworks. The neural network can further include an image network that generates representation data that is combined and weighted with data output by the left, right, and target entity subnetworks to output a sentiment classification for an entity included in a network post.
    Type: Application
    Filed: September 11, 2023
    Publication date: December 28, 2023
    Inventors: Jianfei Yu, Luis Carlos Dos Santos Marujo, Venkata Satya Pradeep Karuturi, Leonardo Ribas Machado das Neves, Ning Xu, William Brendel
  • Multimodal sentiment classification
    Patent number: 11853399
    Abstract: Sentiment classification can be implemented by an entity-level multimodal sentiment classification neural network. The neural network can include left, right, and target entity subnetworks. The neural network can further include an image network that generates representation data that is combined and weighted with data output by the left, right, and target entity subnetworks to output a sentiment classification for an entity included in a network post.
    Type: Grant
    Filed: November 29, 2022
    Date of Patent: December 26, 2023
    Assignee: Snap Inc.
    Inventors: Jianfei Yu, Luis Carlos Dos Santos Marujo, Venkata Satya Pradeep Karuturi, Leonardo Ribas Machado das Neves, Ning Xu, William Brendel
  • MULTIMODAL SENTIMENT CLASSIFICATION
    Publication number: 20230120887
    Abstract: Sentiment classification can be implemented by an entity-level multimodal sentiment classification neural network. The neural network can include left, right, and target entity subnetworks. The neural network can further include an image network that generates representation data that is combined and weighted with data output by the left, right, and target entity subnetworks to output a sentiment classification for an entity included in a network post.
    Type: Application
    Filed: November 29, 2022
    Publication date: April 20, 2023
    Inventors: Jianfei Yu, Luis Carlos Dos Santos Marujo, Venkata Satya Pradeep Karuturi, Leonardo Ribas Machado das Neves, Ning Xu, William Brendel
  • Pictorial symbol prediction
    Patent number: 11620001
    Abstract: Symbol prediction can be implemented using a multi-task system trained for different tasks. The tasks may include a single symbol prediction, symbol category prediction, and symbol subcategory prediction. Categories of symbols can be generated by clustering sets of training data using a clustering scheme.
    Type: Grant
    Filed: August 27, 2020
    Date of Patent: April 4, 2023
    Assignee: Snap Inc.
    Inventors: William Brendel, Francesco Barbieri, Xin Chen, Wei Chu, Venkata Satya Pradeep Karuturi, Luis Carlos Dos Santos Marujo, Leonardo Ribas Machado das Neves
  • Multimodal sentiment classification
    Patent number: 11551042
    Abstract: Sentiment classification can be implemented by an entity-level multimodal sentiment classification neural network. The neural network can include left, right, and target entity subnetworks. The neural network can further include an image network that generates representation data that is combined and weighted with data output by the left, right, and target entity subnetworks to output a sentiment classification for an entity included in a network post.
    Type: Grant
    Filed: August 27, 2019
    Date of Patent: January 10, 2023
    Assignee: Snap Inc.
    Inventors: Jianfei Yu, Luis Carlos Dos Santos Marujo, Venkata Satya Pradeep Karuturi, Leonardo Ribas Machado das Neves, Ning Xu, William Brendel
  • Pictorial symbol prediction
    Patent number: 10788900
    Abstract: Symbol prediction can be implemented using a multi-task system trained for different tasks. The tasks may include a single symbol prediction, symbol category prediction, and symbol subcategory prediction. Categories of symbols can be generated by clustering sets of training data using a clustering scheme.
    Type: Grant
    Filed: June 29, 2018
    Date of Patent: September 29, 2020
    Assignee: Snap Inc.
    Inventors: William Brendel, Francesco Barbieri, Xin Chen, Wei Chu, Venkata Satya Pradeep Karuturi, Luis Carlos Dos Santos Marujo, Leonardo Ribas Machado das Neves