Patents by Inventor Junheng Wang

Junheng Wang 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).

  • RIGHT-ANGLE TURNING METHOD FOR SMALL-DIAMETER TBM EXPLORATION ADIT EXCAVATION
    Publication number: 20240151143
    Abstract: The present invention discloses a right-angle turning method for small-diameter TBM exploration adit excavation and belongs to the field of geological exploration of water conservancy and hydropower projects.
    Type: Application
    Filed: January 17, 2023
    Publication date: May 9, 2024
    Inventors: Youlin Wang, Yongshun Liu, Junheng Cao, Jian Jiao, Shuwu Li, Xiaoliang He, Jian Bao, Yue Zhao, Zhongqiang Zhao, Xiaoxia Xu, Lei Feng, Nan Chen, Wei Liu, Zhixiang Zhao
  • Systems and methods for training predictive models for autonomous devices
    Patent number: 11762391
    Abstract: Systems and methods for training machine-learned models are provided. A method can include receiving a rasterized image associated with a training object and generating a predicted trajectory of the training object by inputting the rasterized image into a first machine-learned model. The method can include converting the predicted trajectory into a rasterized trajectory that spatially corresponds to the rasterized image. The method can include utilizing a second machine-learned model to determine an accuracy of the predicted trajectory based on the rasterized trajectory. The method can include determining an overall loss for the first machine-learned model based on the accuracy of the predictive trajectory as determined by the second machine-learned model. The method can include training the first machine-learned model by minimizing the overall loss for the first machine-learned model.
    Type: Grant
    Filed: September 9, 2022
    Date of Patent: September 19, 2023
    Assignee: UATC, LLC
    Inventors: Henggang Cui, Junheng Wang, Sai Bhargav Yalamanchi, Mohana Prasad Sathya Moorthy, Fang-Chieh Chou, Nemanja Djuric
  • Systems and Methods for Training Predictive Models for Autonomous Devices
    Publication number: 20230021034
    Abstract: Systems and methods for training machine-learned models are provided. A method can include receiving a rasterized image associated with a training object and generating a predicted trajectory of the training object by inputting the rasterized image into a first machine-learned model. The method can include converting the predicted trajectory into a rasterized trajectory that spatially corresponds to the rasterized image. The method can include utilizing a second machine-learned model to determine an accuracy of the predicted trajectory based on the rasterized trajectory. The method can include determining an overall loss for the first machine-learned model based on the accuracy of the predictive trajectory as determined by the second machine-learned model. The method can include training the first machine-learned model by minimizing the overall loss for the first machine-learned model.
    Type: Application
    Filed: September 9, 2022
    Publication date: January 19, 2023
    Inventors: Henggang Cui, Junheng Wang, Sai Bhargav Yalamanchi, Mohana Prasad Sathya Moorthy, Fang-Chieh Chou, Nemanja Djuric
  • Systems and methods for training predictive models for autonomous devices
    Patent number: 11442459
    Abstract: Systems and methods for training machine-learned models are provided. A method can include receiving a rasterized image associated with a training object and generating a predicted trajectory of the training object by inputting the rasterized image into a first machine-learned model. The method can include converting the predicted trajectory into a rasterized trajectory that spatially corresponds to the rasterized image. The method can include utilizing a second machine-learned model to determine an accuracy of the predicted trajectory based on the rasterized trajectory. The method can include determining an overall loss for the first machine-learned model based on the accuracy of the predictive trajectory as determined by the second machine-learned model. The method can include training the first machine-learned model by minimizing the overall loss for the first machine-learned model.
    Type: Grant
    Filed: February 6, 2020
    Date of Patent: September 13, 2022
    Assignee: UATC, LLC
    Inventors: Henggang Cui, Junheng Wang, Sai Bhargav Yalamanchi, Mohana Prasad Sathya Moorthy, Fang-Chieh Chou, Nemanja Djuric
  • Systems and Methods for Training Predictive Models for Autonomous Devices
    Publication number: 20210181754
    Abstract: Systems and methods for training machine-learned models are provided. A method can include receiving a rasterized image associated with a training object and generating a predicted trajectory of the training object by inputting the rasterized image into a first machine-learned model. The method can include converting the predicted trajectory into a rasterized trajectory that spatially corresponds to the rasterized image. The method can include utilizing a second machine-learned model to determine an accuracy of the predicted trajectory based on the rasterized trajectory. The method can include determining an overall loss for the first machine-learned model based on the accuracy of the predictive trajectory as determined by the second machine-learned model. The method can include training the first machine-learned model by minimizing the overall loss for the first machine-learned model.
    Type: Application
    Filed: February 6, 2020
    Publication date: June 17, 2021
    Inventors: Henggang Cui, Junheng Wang, Sai Bhargav Yalamanchi, Mohana Prasad Sathya Moorthy, Fang-Chieh Chou, Nemanja Djuric