Patents by Inventor Yujia SHI

Yujia SHI 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: 11373055
    Abstract: The present disclosure provides a bidirectional attention-based image-text cross-modal retrieval method, applicable for cross-modal retrieval between natural image and electronic text. The present disclosure extracts initial image and text features by using a neural network, and builds a bidirectional attention module to reconstruct the initial image and text features extracted by the neural network, the reconstructed features containing richer semantic information. By using the bidirectional attention module, the present disclosure improves the conventional feature extraction process, obtaining higher-order features with richer image and text semantics, thereby realizing image-text cross-modal retrieval.
    Type: Grant
    Filed: June 22, 2020
    Date of Patent: June 28, 2022
    Assignee: XIDIAN UNIVERSITY
    Inventors: Jing Liu, Yujia Shi
  • Publication number: 20210012150
    Abstract: The present disclosure provides a bidirectional attention-based image-text cross-modal retrieval method, applicable for cross-modal retrieval between natural image and electronic text. The present disclosure extracts initial image and text features by using a neural network, and builds a bidirectional attention module to reconstruct the initial image and text features extracted by the neural network, the reconstructed features containing richer semantic information. By using the bidirectional attention module, the present disclosure improves the conventional feature extraction process, obtaining higher-order features with richer image and text semantics, thereby realizing image-text cross-modal retrieval.
    Type: Application
    Filed: June 22, 2020
    Publication date: January 14, 2021
    Inventors: Jing LIU, Yujia SHI