Patents by Inventor Chaoqun DU

Chaoqun DU 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: 11422057
    Abstract: A dynamic five-hole probe includes a pressure sensing part, a pressure measuring hole transition section, a pressure acquisition section, dynamic pressure sensors and flexible wall pressure buffering tubes, the pressure sensing part being provided with pressure measuring holes to sense three dimensional dynamic pressure components of an airflow; the pressure measuring hole transition section transits from an inlet end surface five-hole structure into an outlet end surface five-hole structure; the pressure acquisition section has therein a centrally symmetric pressure measuring hole structure; pressure sensor mounting holes are in communication with the five pressure measuring holes; each of the dynamic pressure sensors is mounted in a corresponding one of the sensor mounting holes to measure a dynamic pressure of the airflow. The pressure sensing part may have a diameter of 3 mm or less.
    Type: Grant
    Filed: October 31, 2017
    Date of Patent: August 23, 2022
    Inventors: Sichen Wang, Juan Du, Fan Li, Zhiting Tong, Chaoqun Nie, Hongwu Zhang
  • Publication number: 20220237883
    Abstract: An image processing method and apparatus and a storage medium, wherein the method particularly includes firstly acquiring an image-to-be-trained sample and a label segmentation image corresponding to the image-to-be-trained sample; inputting the image-to-be-trained sample into an image segmentation model to be trained, obtaining a first image feature of a last one output layer in the image segmentation model and a second image feature of a second last output layer when the image-to-be-trained sample is being extracted by using the image segmentation model, outputting the corresponding segmented-image samples; based on the label segmentation image and the segmented-image samples, calculating the model loss function, optimizing the model parameter, and generating the image segmentation model that has been optimized; and inputting an acquired image to be processed into the image segmentation model that has been optimized, and generating segmented images corresponding to the image to be processed.
    Type: Application
    Filed: December 27, 2021
    Publication date: July 28, 2022
    Applicant: Tsinghua University
    Inventors: Gao HUANG, Shiji SONG, Chaoqun DU