Patents by Inventor Yanyan SHEN

Yanyan SHEN 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: 20240029866
    Abstract: The present application provides an image-driven brain atlas construction method and apparatus, a device and a storage medium, and involves in the field of medical imaging technologies. The method includes: acquiring a node feature matrix, where the node feature matrix includes time sequences of multiple nodes of a brain; performing hypergraph data structure transformation on the node feature matrix to acquire a first hypergraph incidence matrix; inputting the first hypergraph incidence matrix and the node feature matrix into a trained hypergraph transition matrix generator for processing to output and acquire a first hypergraph transition matrix, where the first hypergraph transition matrix characterizes a constructed multi-modal brain atlas. The technical solution provided by the present application can construct the multi-modal brain atlas, and this multi-modal brain connection structure can express more feature information.
    Type: Application
    Filed: February 7, 2021
    Publication date: January 25, 2024
    Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY
    Inventors: Shuqiang WANG, Junren PAN, Yanyan SHEN
  • Publication number: 20230343026
    Abstract: A method and a device for a three-dimensional reconstruction of brain structure, and terminal equipment. The method includes steps of: obtaining a 2D image of a brain, inputting the 2D image of the brain into a 3D brain point-cloud reconstruction model that has been trained to be processed, and outputting a 3D point-cloud of the brain. The 3D brain point-cloud reconstruction model includes a ResNet encoder and a graphic convolutional neural network. The ResNet encoder is configured to extract a coding feature vector of the 2D image of the brain, and the graphic convolutional neural network is configured to construct the 3D point-cloud of the brain according to the coding feature vector.
    Type: Application
    Filed: January 8, 2021
    Publication date: October 26, 2023
    Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES
    Inventors: Shuqiang WANG, Bowen HU, Yanyan SHEN
  • Patent number: 11661421
    Abstract: The invention provides an indolizine compound represented by formula I or a pharmaceutically acceptable salt thereof, a preparation method and a use thereof. The indolizine compound has an inhibitory effect on wild-type and/or mutant EZH2 or EZH1, and is expected to be developed into a novel drug for anti-tumor or for the treatment of autoimmune diseases.
    Type: Grant
    Filed: March 5, 2019
    Date of Patent: May 30, 2023
    Assignee: HAIHE BIOPHARMA CO., LTD.
    Inventors: Xuxing Chen, Yi Chen, Ying Huang, Meiyu Geng, Qiong Zhang, Jian Ding, Yucai Yao, Qianqian Shen, Yanyan Shen
  • Publication number: 20230032472
    Abstract: The present application provides a method and an apparatus for reconstructing a medical image, and a method and an apparatus for training a medical image reconstruction network. The method for training a medical image reconstruction network includes: performing feature coding extraction on a real image sample to obtain a feature coding vector of the real image sample; performing, through an image reconstruction network, image reconstruction based on the feature coding vector to obtain a first image, and performing image reconstruction based on a first hidden layer vector of the real image sample to obtain a second image; and performing, through an image discrimination network, image discrimination on the real image sample, the first image, and the second image, and optimizing the image reconstruction network according to an image discrimination result.
    Type: Application
    Filed: March 17, 2020
    Publication date: February 2, 2023
    Inventors: Shuqiang WANG, Shengye HU, Zhuo CHEN, Yanyan SHEN
  • Publication number: 20220343638
    Abstract: The present application is suitable for use in the technical field of computers, and provides a smart diagnosis assistance method and terminal based on medical images, comprising: acquiring a medical image to be classified; pre-processing the medical image to be classified to obtain a pre-processed image; and inputting the pre-processed image into a trained classification model for classification processing to obtain a classification type corresponding to the pre-processed image, the classification model comprising tensorized network layers and a second-order pooling module. As the trained classification model comprises tensor decomposed network layers and a second-order pooling module, when processing images on the basis of the classification model, more discriminative features related to pathologies can be extracted, increasing the accuracy of medical image classification.
    Type: Application
    Filed: November 19, 2019
    Publication date: October 27, 2022
    Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES
    Inventors: Shuqiang WANG, Wen YU, Yanyan SHEN, Zhuo CHEN
  • Publication number: 20220148293
    Abstract: An image feature visualization method and apparatus, and an electronic device during model training, inputs the real training data with positive samples into a mapping generator to obtain fictitious training data with negative samples. The mapping generator includes a mapping module configured to learn a key feature map that distinguishes the real training data with positive samples/negative samples, and the fictitious training data with negative samples is generated based on the real training data with positive samples and the key feature map. The training data with negative samples is input into a discriminator to obtain a discrimination result. An optimizer optimizes the mapping generator and the discriminator until training is completed. During model application, a target image that is to be processed is input into the mapping generator, and the mapper in the mapping generator extracts features of the target image.
    Type: Application
    Filed: March 11, 2020
    Publication date: May 12, 2022
    Inventors: Shuqiang WANG, Wen YU, Chenchen XIAO, Shengye HU, Yanyan SHEN
  • Patent number: 11270526
    Abstract: A teaching assistance method and a teaching assistance system using said method, the teaching assistance method comprising implementing behaviour detection of students in classroom images by means of using a trained depth tensor column network model, thus providing higher image recognition precision and reducing the hardware requirements for algorithms, and being able to be used on an embedded device, reducing the usage costs of the teaching assistance method; in addition, a teaching assistance system using said teaching assistance method has the same advantages.
    Type: Grant
    Filed: August 7, 2017
    Date of Patent: March 8, 2022
    Assignees: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES, SHENZHEN SIBIKU TECHNOLOGY CO., LTD
    Inventors: Shuqiang Wang, Yongcan Wang, Yue Yang, Yanyan Shen, Minghui Hu
  • Patent number: 10984289
    Abstract: The present disclosure provides a license plate recognition method, a device thereof, and a user equipment. In the method, a vehicle image is acquired and input to a vehicle searching convolutional neural network (CNN) to search whether there is a vehicle. Then, a license plate image is acquired and input to a license plate searching CNN to search whether there is a license plate. And the license plate image is input to a tensor neural network to detect abnormal or not. Then, a recognition image is acquired and input to judge an area number, letters, and numbers. And an area number image, a letter image, and a number image are output and input to their corresponding recognition CNNs respectively to recognize an area number, letters, and numbers and output respectively. Ultimately, a license plate number recognition result in a form of “area number letter number” are output.
    Type: Grant
    Filed: December 23, 2016
    Date of Patent: April 20, 2021
    Assignee: SHENZHEN INSTITUTE OF ADVANCED TECHNOLOGY
    Inventors: Shuqiang Wang, Dewei Zeng, Yanyan Shen
  • Publication number: 20200399270
    Abstract: The invention provides an indolizine compound represented by formula I or a pharmaceutically acceptable salt thereof, a preparation method and a use thereof. The indolizine compound has an inhibitory effect on wild-type and/or mutant EZH2 or EZH1, and is expected to be developed into a novel drug for anti-tumor or for the treatment of autoimmune diseases.
    Type: Application
    Filed: March 5, 2019
    Publication date: December 24, 2020
    Inventors: Xuxing Chen, Yi Chen, Ying Huang, Meiyu Geng, Qiong Zhang, Jian Ding, Yucai Yao, Qianqian Shen, Yanyan Shen
  • Publication number: 20200380366
    Abstract: The present disclosure relates to an enhanced generative adversarial network and a target sample recognition method. The enhanced generative adversarial network in the present disclosure includes at least one enhanced generator and at least one enhanced discriminator, where the enhanced generator obtains generated data by processing initial data, and provides the generated data to the enhanced discriminator; the enhanced discriminator processes the generated data and feeds back a classification result to the enhanced generator; the enhanced discriminator includes: a convolution layer, a basic capsule layer, a convolution capsule layer, and a classification capsule layer, and the convolution layer, the basic capsule layer, the convolution capsule layer, and the classification capsule layer are sequentially connected to each other.
    Type: Application
    Filed: August 21, 2020
    Publication date: December 3, 2020
    Inventors: SHUQIANG WANG, YANYAN SHEN, WENYONG ZHANG
  • Patent number: 10748080
    Abstract: A method for processing tensor data for pattern recognition and a computer device are provided. The method includes: constructing a decision function by the optimal projection tensor W which has been rank-one decomposed together with the offset scalar b, and inputting to-be-predicted tensor data which has been rank-one decomposed into the decision function for prediction.
    Type: Grant
    Filed: December 4, 2015
    Date of Patent: August 18, 2020
    Assignee: Shenzhen Institutes of Advanced Technology
    Inventors: Shuqiang Wang, Dewei Zeng, Yanyan Shen, Changhong Shi, Zhe Lu
  • Publication number: 20200193232
    Abstract: The present disclosure provides a license plate recognition method, a device thereof, and a user equipment. In the method, a vehicle image is acquired and input to a vehicle searching convolutional neural network (CNN) to search whether there is a vehicle. Then, a license plate image is acquired and input to a license plate searching CNN to search whether there is a license plate. And the license plate image is input to a tensor neural network to detect abnormal or not. Then, a recognition image is acquired and input to judge an area number, letters, and numbers. And an area number image, a letter image, and a number image are output and input to their corresponding recognition CNNs respectively to recognize an area number, letters, and numbers and output respectively. Ultimately, a license plate number recognition result in a form of “area number letter number” are output.
    Type: Application
    Filed: December 23, 2016
    Publication date: June 18, 2020
    Inventors: SHUQIANG WANG, DEWEI ZENG, YANYAN SHEN
  • Publication number: 20200175264
    Abstract: A teaching assistance method and a teaching assistance system using said method, the teaching assistance method comprising implementing behaviour detection of students in classroom images by means of using a trained depth tensor column network model, thus providing higher image recognition precision and reducing the hardware requirements for algorithms, and being able to be used on an embedded device, reducing the usage costs of the teaching assistance method; in addition, a teaching assistance system using said teaching assistance method has the same advantages.
    Type: Application
    Filed: August 7, 2017
    Publication date: June 4, 2020
    Inventors: SHUQIANG WANG, YONGCAN WANG, YUE YANG, YANYAN SHEN, MINGHUI HU
  • Publication number: 20170344906
    Abstract: Optimization method and system for supervised learning under tensor mode is provided; wherein the method includes: receiving an input training tensor data set; introducing a within class scatter matrix into an objective function such that between class distance is maximized, at the same time, within class distance is minimized by the objective function; constructing an optimal frame of the objective function of an optimal projection tensor machine OPSTM subproblem; constructing an optimal frame of an objective function of an OPSTM problem; solving the revised dual problem and outputting alagrangian optimal combination and an offset scalar b; calculating a projection tensor W*; calculating a optimal projection tensor W; by the W together with the b, constructing a decision function; inputting to-be-predicted tensor data which has been rank-one decomposed into the decision function for prediction.
    Type: Application
    Filed: December 4, 2015
    Publication date: November 30, 2017
    Inventors: Shuqiang WANG, Dewei ZENG, Yanyan SHEN, Changhong SHI, Zhe LU