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191.发明申请公开(公告)号：US20230136882A1
公开(公告)日：2023-05-04
申请号：US18088743
申请日：2022-12-26
Applicant: ZHEJIANG LAB
Inventor： Qingshui GUO , Kun YIN , Chen JI , Jihou WANG , Xiaojun YING
Abstract: Discloses a coherent microwave photonics radar detection method and system based on injection locking frequency multiplication. The method uses a baseband signal to modulate an optical carrier to generate a modulated optical signal including a plurality of high-order sidebands; the modulated optical signal is divided into two paths which are respectively injected into two slave lasers for high-order sideband injection locking to obtain two locked sideband optical signals; Based on combining and splitting two locked sideband optical signals, the radar transmitting signal and receiving optical signal can be obtained through photo-detection and electro-optic modulation. After coherent detection of receiving optical signal, obtaining the intermediate frequency signal, and detection target information can be extracted from intermediate frequency signal by radar algorithm.
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公开(公告)号：US20230076457A1
公开(公告)日：2023-03-09
申请号：US17888513
申请日：2022-08-16
Applicant: Zhejiang Lab
Inventor： Feng GAO , Wenyuan BAI
Abstract: The present invention discloses an edge calculation-oriented reparametric neural network architecture search method, including the following steps: S1: designing linear operators and multi-branch block structures; S2: constructing a hypernetwork by stacking the multi-branch block structures; S3: training the hypernetwork through a gradient-based first-stage search algorithm; S4: deleting redundant branches in the hypernetwork to construct an optimal subnetwork; S5: converting the multi-branch optimal subnetwork into a single-branch network; and S6: completing task reasoning by using the single-branch network. The method is used to search the neural network structure capable of performing reparameterization, and ensures the reasoning real-time performance and the high efficiency of model operation while ensuring the reasoning precision.
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193.发明授权公开(公告)号：US11526774B2
公开(公告)日：2022-12-13
申请号：US17564071
申请日：2021-12-28
Applicant: ZHEJIANG LAB
Inventor： Hongsheng Wang , Haijun Shan , Jiaqing Fu
Abstract: Disclosed is a method for automatically compressing multi-task oriented pre-trained language model and a platform thereof. According to the method, a meta-network of a structure generator is designed, a knowledge distillation coding vector is constructed based on a knowledge distillation method of Transformer layer sampling, and a distillation structure model corresponding to a currently input coding vector is generated by using the structure generator; at the same time, a Bernoulli distribution sampling method is provided for training the structure generator; in each iteration, each encoder unit is transferred by Bernoulli distribution sampling to form a corresponding coding vector; by changing the coding vector input to the structure generator and a small batch of training data, the structure generator and the corresponding distillation structure are jointly trained, and a structure generator capable of generating weights for different distillation structures can be acquired.
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公开(公告)号：US20220383565A1
公开(公告)日：2022-12-01
申请号：US17616161
申请日：2021-01-23
Applicant: ZHEJIANG LAB , MINFOUND MEDICAL SYSTEMS CO., LTD
Inventor： Wentao ZHU , Bao YANG , Long ZHOU , Hongwei YE , Ling CHEN , Fan RAO , Yaofa WANG
IPC: G06T11/00
Abstract: Disclosed is a three-dimensional low-dose PET reconstruction method based on deep learning. The method comprises the following steps: back projecting low-dose PET raw data to the image domain to maintain enough information from the raw data; selecting an appropriate three-dimensional deep neural network structure to fit the mapping between the back projection of the low-dose PET and a standard-dose PET image; after learning from the training samples the network parameters are fixed, realizing three-dimensional PET image reconstruction starting from low-dose PET raw data, thereby obtaining a low-dose PET reconstructed image which has a lower noise and a higher resolution compared with the traditional reconstruction algorithm and image domain noise reduction processing.
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195.发明申请公开(公告)号：US20220344070A1
公开(公告)日：2022-10-27
申请号：US17695865
申请日：2022-03-16
Applicant: ZHEJIANG LAB , ZHEJIANG UNIVERSITY
Inventor： Cuihong LI , Zhiming CHEN , Yuanyuan MA , Xiaowen GAO , Zhenhai FU , Huizhu HU
Abstract: Disclosed is a multi-dimensional optical tweezers calibration device based on electric field quantity calibration and a method thereof. The polarization-dependent characteristics of a tightly focused optical trap are utilized to realize triaxial electric field force calibration of particles through a one-dimensional electric field quantity calibration device. The method of the present application enables a particle electric field force calibration system to be compatible with particle delivery and particle detection systems; the device is simplified and calibration complexity is reduced.
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Patent Agency Ranking
公开(公告)号：US20220265218A1
公开(公告)日：2022-08-25
申请号：US17571523
申请日：2022-01-09
Applicant: Zhejiang Lab
Inventor： Taihao LI , Guanxiong PEI , Yulong LIU
Abstract: The present invention discloses a real-time evaluation method and evaluation system for group emotion homogeneity. The method comprises the steps as follows: enabling testees to be in the same emotion induction environment, and collecting the original electroencephalograph (EEG) signals of multiple persons at the same time through online multichannel EEG equipment; and based on the average instantaneous phase per second of the beta frequency band and the energy value per second of the alpha frequency band obtained after wavelet transformation, calculating the time synchronization degree and the valence consistency degree in real time, and finally obtaining a group emotion homogeneity index for the objective evaluation of group emotion homogeneity.
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公开(公告)号：US20220138414A1
公开(公告)日：2022-05-05
申请号：US17531813
申请日：2021-11-22
Applicant: ZHEJIANG LAB
Inventor： Hongsheng Wang , Haijun Shan , Shengjian Hu
Abstract: Disclosed is a meta-knowledge fine tuning method and platform for a multi-task language model. The method is to obtain highly transferable shared knowledge, that is, meta-knowledge, on different data sets of tasks of the same category, perform interrelation and mutual reinforcement on the learning processes of the tasks of the same category that correspond to different data sets and are in different domains, so as to improve the fine tuning effect of downstream tasks of the same category on data sets of different domains in the application of the language model, and improve the parameter initialization ability and the generalization ability of a general language model for the tasks of the same category.
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198.发明申请公开(公告)号：US20220093258A1
公开(公告)日：2022-03-24
申请号：US17543738
申请日：2021-12-07
Applicant: ZHEJIANG LAB
Inventor： Jingsong LI , Yu TIAN , Weiguo CHEN , Jing MA
Abstract: Provided is a multi-center synergetic cancer prognosis prediction system based on multi-source migration learning. The system includes a model parameter setting module, a data screening module, and a multi-source migration learning module, wherein the model parameter setting module is responsible for setting cancer prognosis prediction model parameters; the data screening module is arranged at a clinical center, and a management center transmits the set model parameter to each clinical center, such that each clinical center inquires a sample feature and prognosis index data from a local database according to the model parameter, so as to preprocess the data; and the multi-source migration learning module includes a source model training unit, a migration weight calculation unit, and a target model calculation unit.
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199.发明申请公开(公告)号：US20250132810A1
公开(公告)日：2025-04-24
申请号：US19002805
申请日：2024-12-27
Applicant: ZHEJIANG LAB
Inventor： Nan HAO , Xingming ZHANG , Xiangming ZHU , Fujun ZHANG
IPC: H04B7/185 , H04W12/108 , H04W60/00
Abstract: A method and a device for improving pipeline safety of a space-terrestrial network architecture. The method pre-registers the profile of a base station in the network repository function network element of a 5G core network; after receiving a relay pipeline connection establishment request initiated by a base station, a relay satellite sends a network function verification request to the network repository function network element through a network expose function network element; after receiving a response to a network function discovery request of the base station, the network expose function network element sets the corresponding verification result of the base station according to whether there is base station registration information and responds to a verification request of the network element; and finally, the relay satellite verifies the verification result cell carried in the received response to determine the legality of the current access to the base station.
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200.发明申请公开(公告)号：US20250132057A1
公开(公告)日：2025-04-24
申请号：US18600800
申请日：2024-03-11
Applicant: ZHEJIANG LAB
Inventor： Zenghui XU , Ji ZHANG , Yu ZHANG , Ting YU , Jin ZHAO , Linlin HOU , Zhan ZHANG
IPC: G16H50/80
Abstract: An infectious disease infection prediction method, an apparatus, and a storage medium based on macro-micrograph fusion are provided. The method includes: acquiring macrographs of a plurality of first regions and micrographs of second regions within a set period; inputting the macroscopic graphs and the microscopic graphs into two graph convolutional neural networks to obtain two hidden layer vectors respectively, and fusing the two hidden layer vectors to obtain fusion hidden layer information of the first regions; performing a time sequence calculation of the fusion hidden layer information to obtain time sequence hidden layer information of the first regions; inputting the time series hidden layer information into two prediction networks to obtain two prediction results, respectively, and performing fusion calculation of the two prediction results to obtain a final prediction result of infectious diseases in the first regions.
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