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    Vulnerable plaque identification method, application server thereof, and computer readable medium
    1.
    发明授权
    Vulnerable plaque identification method, application server thereof, and computer readable medium 有权

    公开(公告)号：US11094059B2

    公开(公告)日：2021-08-17

    申请号：US16633153

    申请日：2018-06-12

    Applicant: PING AN TECHNOLOGY (SHENZHEN) CO., LTD.

    Inventor： Jianzong Wang ,  Tianbo Wu ,  Lihong Liu ,  Xinhui Liu ,  Jing Xiao

    IPC: G06K9/00 ,  G06T7/00 ,  G06T7/73 ,  G16H30/40 ,  A61B5/00 ,  A61B5/02

    Abstract: The present disclosure publishes a vulnerable plaque identification method. The method includes: receiving an angiocarpy image sent by a terminal device; transforming the angiocarpy image in an original Cartesian coordinate system into a polar coordinate system to form a polarization image; constructing a faster RCNN architecture and accomplishing a training; inputting the polarization image into the faster RCNN architecture accomplished the training to identify the polarization image, and outputting the image with the marked vulnerable plaques; feed backing the image with the marked vulnerable plaques to the terminal device. The present disclosure also publishes an application server and a computer readable medium. The vulnerable plaque identification method, the application server, and the computer readable medium can quickly and correctly conform the position of the vulnerable plaque.

    Method and device for identifying a user interest, and computer-readable storage medium
    2.
    发明授权
    Method and device for identifying a user interest, and computer-readable storage medium 有权

    公开(公告)号：US10977447B2

    公开(公告)日：2021-04-13

    申请号：US16318818

    申请日：2017-09-28

    Applicant: PING AN TECHNOLOGY (SHENZHEN) CO., LTD.

    Inventor： Jianzong Wang ,  Zhangcheng Huang ,  Tianbo Wu ,  Jing Xiao

    IPC: G06F40/279 ,  G06F40/30 ,  G06N20/00 ,  G06F40/166 ,  G06F16/35 ,  G06N5/04

    Abstract: Disclosed is a method for identifying a user interest, including: obtaining training samples and test samples, the training samples being obtained by manually labeling after the corresponding topic models have been trained based on text data; extracting characteristics of the training samples and of the test samples, and computing optimal model parameters of a logistic regression model by an iterative algorithm based on the characteristics of the training samples; evaluating the logistic regression model based on the characteristics of the test samples and an area AUC under an ROC curve to train and obtain a first theme classifier; determining a theme to which the text data belongs using the first theme classifier, computing a score of the theme to which the text data belongs based on the logistic regression model, and computing a confidence score of the user being interested in the theme according to a second preset algorithm. Further disclosed are a device for identifying a user interest and a computer-readable storage medium.

    SPEECH RECOGNITION METHOD, APPARATUS, AND COMPUTER READABLE STORAGE MEDIUM
    3.
    发明申请
    SPEECH RECOGNITION METHOD, APPARATUS, AND COMPUTER READABLE STORAGE MEDIUM 有权

    公开(公告)号：US20210074264A1

    公开(公告)日：2021-03-11

    申请号：US16642371

    申请日：2017-11-28

    Applicant: PING AN TECHNOLOGY (SHENZHEN) CO., LTD.

    Inventor： Hao Liang ,  Ning Cheng ,  Jianzong Wang ,  Jing Xiao

    IPC: G10L15/06 ,  G10L15/02 ,  G10L15/16 ,  G10L15/18

    Abstract: Disclosed are a speech recognition method, apparatus, computer device and storage medium. The method includes: performing a framing and an acoustic feature extraction of a speech-information-to-be-tested according to a default rule to obtain a frame-level speech feature sequence; dividing the frame-level speech feature sequence into n blocks sequentially; inputting all blocks into a preset bidirectional LSTM-RNN model parallelly to obtain an output result of the corresponding neuron in an output layer of the preset bidirectional LSTM-RNN model corresponding to the forward recognition result and backward recognition result of each block to obtain a speech recognition result of the speech-information-to-be-tested. The present application can improve the speech recognition effect significantly and reduce the time delay of the speech decoding effectively.

    Car damage picture angle correction method, electronic device, and readable storage medium
    4.
    发明授权
    Car damage picture angle correction method, electronic device, and readable storage medium 有权

    公开(公告)号：US11386499B2

    公开(公告)日：2022-07-12

    申请号：US16084993

    申请日：2017-09-30

    Applicant: Ping An Technology (Shenzhen) Co., Ltd.

    Inventor： Jianzong Wang ,  Chenyu Wang ,  Jin Ma ,  Jing Xiao

    IPC: G06Q40/08 ,  G06K9/62 ,  G06T3/60 ,  G06T7/30 ,  G06V20/13

    Abstract: Disclosed are a car damage picture angle correction method, an electronic device, and a readable storage medium. The method includes: after receiving a car damage picture to be classified and identified, identifying a rotation category corresponding to the received car damage picture by using a pre-trained picture rotation category identification model; determining a rotation control parameter corresponding to the identified rotation category according to a pre-determined mapping relation between rotation categories and rotation control parameters, the rotation control parameter including a rotation angle and a rotation direction; and rotating the received car damage picture according to the determined rotation control parameter, so as to generate an angle-normal car damage picture. The disclosure can perform car damage picture angle correction more comprehensively and more effectively with no need to artificially perform angle identification on a car damage picture and to manually rotate the picture, thereby achieving a higher efficiency and accuracy.

    Speech recognition with trained GMM-HMM and LSTM models
    6.
    发明授权
    Speech recognition with trained GMM-HMM and LSTM models 有权

    公开(公告)号：US11062699B2

    公开(公告)日：2021-07-13

    申请号：US16348807

    申请日：2017-08-31

    Applicant: PING AN TECHNOLOGY(SHENZHEN) CO., LTD.

    Inventor： Hao Liang ,  Jianzong Wang ,  Ning Cheng ,  Jing Xiao

    IPC: G10L15/00 ,  G10L15/20 ,  G10L17/00 ,  G10L15/14 ,  G06F17/16 ,  G06F17/18 ,  G06N3/08 ,  G10L15/16 ,  G10L15/02

    Abstract: A speech recognition method, comprising: acquiring speech data to be recognized; extracting a Filter Bank feature and a Mel-Frequency Cepstral Coefficient (MFCC) feature in the speech data; using the MFCC feature as input data of a trained Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) model, acquiring a first likelihood probability matrix outputted by the trained GMM-HMM model; using the Filter Bank feature as an input feature of a trained long short-term memory (LSTM) model which has a connection unit, acquiring a posterior probability matrix outputted by the LSTM model; using the posterior probability matrix and the first likelihood probability matrix as input data of a trained HMM model, acquiring an second likelihood probability matrix; and acquiring a target word sequence corresponding to the speech data to be recognized from a phoneme decoding network according to the second likelihood probability matrix.

    Acoustic model training method, speech recognition method, apparatus, device and medium
    7.
    发明授权
    Acoustic model training method, speech recognition method, apparatus, device and medium 有权

    公开(公告)号：US11030998B2

    公开(公告)日：2021-06-08

    申请号：US16097850

    申请日：2017-08-31

    Applicant: Ping An Technology (Shenzhen) Co., Ltd.

    Inventor： Hao Liang ,  Jianzong Wang ,  Ning Cheng ,  Jing Xiao

    IPC: G10L15/14 ,  G10L15/02 ,  G10L15/16

    Abstract: An acoustic model training method, a speech recognition method, an apparatus, a device and a medium. The acoustic model training method comprises: performing feature extraction on a training speech signal to obtain an audio feature sequence; training the audio feature sequence by a phoneme mixed Gaussian Model-Hidden Markov Model to obtain a phoneme feature sequence; and training the phoneme feature sequence by a Deep Neural Net-Hidden Markov Model-sequence training model to obtain a target acoustic model. The acoustic model training method can effectively save time required for an acoustic model training, improve the training efficiency, and ensure the recognition efficiency.

    Method, system, electronic device, and medium for classifying license plates based on deep learning
    10.
    发明授权
    Method, system, electronic device, and medium for classifying license plates based on deep learning 有权

    公开(公告)号：US10528841B2

    公开(公告)日：2020-01-07

    申请号：US15737318

    申请日：2017-06-23

    Applicant: PING AN TECHNOLOGY (SHENZHEN) CO., LTD.

    Inventor： Jianzong Wang ,  Ming Liu ,  Jing Xiao

    IPC: G06K9/62 ,  G06K9/32 ,  G06N3/04 ,  G06N3/08 ,  G06N5/04 ,  G08G1/017

    Abstract: The present invention discloses a method, a system, an electronic device, and a medium for classifying license plates based on deep learning that are applied to an electronic device. The method includes: acquiring at least one photograph sent by a terminal device; preprocessing the acquired photograph such that the preprocessed photograph matches a plurality of input parameters of a pre-trained recognition model; and inputting the preprocessed photograph to the pre-trained recognition model to recognize corresponding vehicle use information of the photograph, and sending the corresponding vehicle use information of the photograph to the terminal device. Thus, with this disclosure, the use of a vehicle in a photograph can be automatically and accurately recognized and further the photographs can be accurately classified, thereby improving the accuracy as well as the efficiency.

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