Patents by Inventor Abner Ayala Acevedo

Abner Ayala Acevedo 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).

  • Tuning layers of a modular neural network
    Patent number: 11866055
    Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), based on input from one or more of the cameras and/or other sensors, to intelligently detect safety events in real-time. The one or more neural networks may be an ensemble neural network that includes neural networks for detecting a head and hand of a user, neural networks for detecting hand actions of the user, neural networks for detecting the head pose of the user, neural networks for predicting an occurrence of an event, and neural networks for predicting a start time and end time of the event. Further, the neural networks can be segmented into a modular neural network based on metadata. The segmentation of the neural network can define a thin layer of the modular neural network to enable independent tuning of the thin layer of the modular neural network.
    Type: Grant
    Filed: May 9, 2022
    Date of Patent: January 9, 2024
    Assignee: Samsara Inc.
    Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
  • Refining event triggers using machine learning model feedback
    Patent number: 11780446
    Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. The vehicle device may further pass the input to a backend server for further analysis and the backend server can detect safety events based on the input. The vehicle device may analyze the output of the vehicle device and the output of the backend server to determine whether the output of the vehicle device is correct. If the output of the vehicle device is incorrect, the vehicle device can adjust how the vehicle device identifies safety events.
    Type: Grant
    Filed: May 2, 2022
    Date of Patent: October 10, 2023
    Assignee: Samsara Inc.
    Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
  • Ensemble neural network state machine for detecting distractions
    Patent number: 11386325
    Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), based on input from one or more of the cameras and/or other sensors, to intelligently detect safety events in real-time. The one or more neural networks may be an ensemble neural network that includes neural networks for detecting a head and hand of a user, neural networks for detecting hand actions of the user, neural networks for detecting the head pose of the user, neural networks for predicting an occurrence of an event, and neural networks for predicting a start time and end time of the event. Further, the neural networks can be segmented into a modular neural network based on metadata. The segmentation of the neural network can define a thin layer of the modular neural network to enable independent tuning of the thin layer of the modular neural network.
    Type: Grant
    Filed: November 12, 2021
    Date of Patent: July 12, 2022
    Assignee: Samsara Inc.
    Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
  • Refining event triggers using machine learning model feedback
    Patent number: 11352013
    Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), such as based on input from one or more of the cameras and/or other sensors associated with the dash cam, to intelligently detect safety events in real-time. The vehicle device may further pass the input to a backend server for further analysis and the backend server can detect safety events based on the input. The vehicle device may analyze the output of the vehicle device and the output of the backend server to determine whether the output of the vehicle device is correct. If the output of the vehicle device is incorrect, the vehicle device can adjust how the vehicle device identifies safety events.
    Type: Grant
    Filed: November 12, 2021
    Date of Patent: June 7, 2022
    Assignee: Samsara Inc.
    Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh
  • Tuning layers of a modular neural network
    Patent number: 11352014
    Abstract: A vehicle device may execute one or more neural networks (and/or other artificial intelligence), based on input from one or more of the cameras and/or other sensors, to intelligently detect safety events in real-time. The one or more neural networks may be an ensemble neural network that includes neural networks for detecting a head and hand of a user, neural networks for detecting hand actions of the user, neural networks for detecting the head pose of the user, neural networks for predicting an occurrence of an event, and neural networks for predicting a start time and end time of the event. Further, the neural networks can be segmented into a modular neural network based on metadata. The segmentation of the neural network can define a thin layer of the modular neural network to enable independent tuning of the thin layer of the modular neural network.
    Type: Grant
    Filed: November 12, 2021
    Date of Patent: June 7, 2022
    Assignee: Samsara Inc.
    Inventors: Sharan Srinivasan, Brian Tuan, John Bicket, Jing Wang, Muhammad Ali Akhtar, Abner Ayala Acevedo, Bruce Kellerman, Vincent Shieh