Patents by Inventor Juanru Cheng

Juanru Cheng 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: 20250087082
    Abstract: Provided are a digital twinning method and system for a scene flow based on a dynamic trajectory flow, which belong to the field of traffic control. The method includes: extracting and identifying a target semantic trajectory with a detecting and tracking integrated multi-modal fusion and perception enhancement network; extracting road traffic semantics, so as to obtain a highly parameterized virtual road layout top view; obtaining a road layout traffic semantic grid encoding vector based on the virtual road layout top view; constructing a target coupling relation model; constructing a traffic force constraint model; constructing a long short term memory trajectory prediction network; predicting a motion trajectory of a target with the long short term memory trajectory prediction network, so as to obtain the predicted motion trajectory; and obtaining a digital twin of the scene flow based on trajectory extraction, semantic identification and the predicted motion trajectory.
    Type: Application
    Filed: March 22, 2023
    Publication date: March 13, 2025
    Inventors: Zhanwen LIU, Xing FAN, Shan LIN, Chao LI, Jun ZHAI, Yanming Fang, Songhua FAN, Zijian WANG, Nan YANG, Zhibiao XUE, Jin FAN, Juanru CHENG, Yuande JIANG, Litong ZHANG
  • Publication number: 20250037299
    Abstract: A 3D target detection method based on multimodal fusion and a depth attention mechanism includes the following steps: obtaining and preprocessing original point cloud data and original image data; inputting the preprocessed point cloud data and image data into a 3D target detection network based on multimodal fusion and the depth attention mechanism, where the 3D target detection network based on multimodal fusion and the depth attention mechanism includes a generation phase for 3D bounding box proposals and a refinement phase for 3D bounding boxes, and the network outputs parameters and classification confidence of a target bounding box; training the 3D target detection network based on multimodal fusion and the depth attention mechanism; and processing the collected lidar point cloud data and image data by using the trained detection network, and outputting 3D target information, to realize 3D target detection.
    Type: Application
    Filed: October 10, 2024
    Publication date: January 30, 2025
    Inventors: Zhanwen Liu, Yang Wang, Xing Fan, Shan Lin, Juanru Cheng, Yuande Jiang, Chao Li, Bolin Gao, Yi He, Jin Fan, Nan Yang