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公开(公告)号：US11194972B1
公开(公告)日：2021-12-07
申请号：US17464421
申请日：2021-09-01
Inventor： Jianhua Tao , Ke Xu , Bin Liu , Yongwei Li
IPC: G06F17/00 , G06F40/30 , G06F40/284 , G06N3/04
Abstract: Disclosed is a semantic sentiment analysis method fusing in-depth features and time sequence models, including: converting a text into a uniformly formatted matrix of word vectors; extracting local semantic emotional text features and contextual semantic emotional text features from the matrix of word vectors; weighting the local semantic emotional text features and the contextual semantic emotional text features by using an attention mechanism to generate fused semantic emotional text features; connecting the local semantic emotional text features, the contextual semantic emotional text features and the fused semantic emotional text features to generate global semantic emotional text features; and performing final text emotional semantic analysis and recognition by using a softmax classifier and taking the global semantic emotional text features as input.
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公开(公告)号：US11134064B2
公开(公告)日：2021-09-28
申请号：US16316290
申请日：2018-06-07
Inventor： Xianda Liu , Tianyu Wang , Jianming Zhao , Bowen Zhang , Peng Zeng , Haibin Yu
Abstract: The present invention relates to a network guard unit for an industrial embedded system and a guard method. The specific method is to form the network guard unit (NGU) through security technologies, such as integrated access control, identity authentication and communication data encryption, to provide active guard for a site control device. The NGU comprises an access control module, an identity authentication module, a data encryption module, a key negotiation module and a PCIE communication module, and supports the communication modes of dual network cards and PCIE bus. The present invention builds a secure and trusted operating environment for industrial control systems in combination with an active guard technical means in the field of information security on the basis of ensuring the correctness and the feasibility of security of various terminal devices in the industrial control systems.
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123.发明申请公开(公告)号：US20210282694A1
公开(公告)日：2021-09-16
申请号：US16961700
申请日：2016-11-03
Inventor： Tianzi JIANG , Xin ZHANG , Nianming ZUO , Juanning SI
Abstract: A neurovascular coupling analytical method based on an electroencephalogram and functional near-infrared spectroscopy includes: S100: acquiring an electroencephalogram signal and a brain hemodynamic signal; S110: extracting an event-related potential signal from the electroencephalogram signal; S120: extracting a time characteristic from the event-related potential signal; S130: extracting a hemodynamic response function from the brain hemodynamic signal; S140: extracting an amplitude characteristic and time characteristics from the hemodynamic response function; and S150: analyzing influence of the time characteristic of the event-related potential signal on the amplitude characteristic and the time characteristics of the hemodynamic response function to obtain a coupling result. The time characteristic of the event-related potential signal is a delay. The amplitude characteristic of the hemodynamic response function is a peak amplitude, and the time characteristics of the hemodynamic response function comprises a rising delay, a peak time, and a full width at half maximum.
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124.发明申请公开(公告)号：US20210224609A1
公开(公告)日：2021-07-22
申请号：US16960072
申请日：2019-12-10
Inventor： Guodong YANG , Yunong TIAN , En LI , Zize LIANG , Min TAN , Fengshui JING , Zishu GAO , Hao WANG , Yuansong SUN , Sixi LU
Abstract: A multi-label object detection method based on an object detection network includes: selecting an image of an object to be detected as an input image; based on a trained object detection network, obtaining a class of the object to be detected, coordinates of a center of the object to be detected, and a length and a width of a detection rectangular box according to the input image; and outputting the class of the object to be detected, the coordinates of the center of the object to be detected, and the length and the width of the detection rectangular box. The method of the present invention can perform real-time and accurate object detection on different classes of objects with improved detection speed and accuracy, and can solve the problem of object overlapping and occlusion during the object detection.
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125.发明授权公开(公告)号：US10939845B2
公开(公告)日：2021-03-09
申请号：US16907334
申请日：2020-06-22
Inventor： Jie Tian , Peng Zhang , Hui Hui , Kun Wang , Xin Yang
IPC: A61B5/0515 , A61B5/00
Abstract: A FFL-based magnetic particle imaging three-dimensional reconstruction method includes: acquiring current signal data of an induction coil during FFL-based three-dimensional scanning process of a scanned object; based on the current signal data, performing deconvolution through a preset kernel function to acquire a two-dimensional image data set, wherein the kernel function is a step function with L2 regularized constraint; based on the two-dimensional image data set, acquiring an initial three-dimensional image by using a Wiener filtering deconvolution algorithm; and based on the initial three-dimensional image, performing deconvolution through a Langevin function, and acquiring a final three-dimensional image by Radon transformation. A FFL-based magnetic particle imaging three-dimensional reconstruction system includes a magnet group, an induction coil, an imaging bed, and a control and imaging device, wherein, a magnetic particle imaging method in the control and imaging device is the FFL-based magnetic particle imaging three-dimensional reconstruction method.
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Patent Agency Ranking
公开(公告)号：US20210065021A1
公开(公告)日：2021-03-04
申请号：US16636736
申请日：2019-02-21
Inventor： Wenli SHANG , Peng ZENG , Xianda LIU , Jianming ZHAO , Long YIN , Chunyu CHEN , Jiansong AO , Guoyu TONG
Abstract: The present invention relates to a working condition state modeling and model correcting method, comprising collecting data, and arranging the data in a chronological order to form a time sequence data set; preprocessing the time sequence data set; clustering the preprocessed time sequence data set, computing a central point data set of the duster, and generating a working condition data set and a working condition process data set; counting a working condition transition probability for the working condition process data set to form a working condition transition probability model data set; collecting the data, and detecting and processing the data; computing a working condition state transition mode phase by phase and processing. The present invention is based on a counting modeling method, introduces expert prior knowledge to correct the established model gradually, enables the model range to cover the overall system working condition state and solves the problem of low coverage rage in the mechanism analysis modeling methods and the counting modeling method, The present invention can be used as the input of an abnormal working condition diagnosis method, and can effectively improve the accuracy rate of abnormality diagnosis.
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公开(公告)号：US20210012093A1
公开(公告)日：2021-01-14
申请号：US17038208
申请日：2020-09-30
Inventor： Qiang RAO , Bing YU , Bailan FENG , Yibo HU , Xiang WU , Ran HE , Zhenan SUN
Abstract: This application provides a method and an apparatus for generating a face rotation image. The method includes: performing pose encoding on an obtained face image based on two or more landmarks in the face image, to obtain pose encoded images; obtaining a plurality of training images each including a face from a training data set, where presented rotation angles of the faces included in the plurality of training images are the same; performing pose encoding on a target face image based on two or more landmarks in the target face image in the foregoing similar manner, to obtain pose encoded images, where the target face image is obtained based on the plurality of training images; generating a to-be-input signal based on the face image and the foregoing two types of pose encoded images; and inputting the to-be-input signal into an face rotation image generative model to obtain a face rotation image.
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公开(公告)号：US10722416B2
公开(公告)日：2020-07-28
申请号：US15559819
申请日：2015-03-20
Inventor： Zengguang Hou , Weiqun Wang , Long Peng , Xu Liang , Liang Peng , Long Cheng , Xiaoliang Xie , Guibin Bian , Min Tan , Lincong Luo
Abstract: The application presents a multi-posture lower limb rehabilitation robot, which includes a robot base and a training bed. The training bed comprises two sets of leg mechanisms, a seat, a seat width adjustment mechanism, a mechanism for adjusting the gravity center of human body, a back cushion, a weight support system and a mechanism for adjusting the back cushion angle. The robot base comprises a mechanism for adjusting the bed angle. The mechanisms for adjusting the angles of bed and back cushion can be used together to provide paralysis patients with multiple training modes of lying, sitting, and standing postures. Each leg mechanism comprises hip, knee, and ankle joints, which are driven by electric motors; angle and force sensors are installed on each joint, and can be used to identify patients' motion intention to provide patients with active and assistant training. The mechanism for adjusting the gravity center of human body, the leg mechanisms, and the weight support system can be used together to implement human natural walking gait to improve the training effect.
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129.发明授权公开(公告)号：US10685434B2
公开(公告)日：2020-06-16
申请号：US16068912
申请日：2016-03-30
Inventor： Kaiqi Huang , Tieniu Tan , Ran He , Yueying Kao
Abstract: The present application discloses a method for assessing aesthetic quality of a natural image based on multi-task deep learning. Said method includes: step 1: automatically learning aesthetic and semantic characteristics of the natural image based on multi-task deep learning; step 2: performing aesthetic categorization and semantic recognition to the results of automatic learning based on multi-task deep learning, thereby realizing assessment of aesthetic quality of the natural image. The present application uses semantic information to assist learning of expressions of aesthetic characteristics so as to assess aesthetic quality more effectively, besides, the present application designs various multi-task deep learning network structures so as to effectively use the aesthetic and semantic information for obtaining highly accurate image aesthetic categorization. The present application can be applied to many fields relating to image aesthetic quality assessment, including image retrieval, photography and album management, etc.
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公开(公告)号：US10460833B2
公开(公告)日：2019-10-29
申请号：US15512781
申请日：2014-09-19
Inventor： Tianzi Jiang , Nianming Zuo , Xin Zhang , Yujin Zhang , Hao Liu
IPC: G16H10/00 , A61B5/00 , A61B5/0476 , G06F3/06 , A61B5/1455 , G16H40/63 , G16H10/60
Abstract: A method for storing data of photoelectrically synchronous brain activity recording, said method comprising: generating data when a photoelectrically synchronous brain activity detection system is operating; generating from said data a data storage file comprising a basic information data segment, a near-infrared spectrum data segment and a brain electrical activity data segment, and sequentially storing said data segments into a .neg file in binary form according to the above order. The method can store comprehensive test information, flexibly configure the near-infrared and brain electrical measurement information, and realize synchronous storage of near-infrared data and brain electrical data and maintain file version compatibility.
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