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公开(公告)号：US20250157045A1
公开(公告)日：2025-05-15
申请号：US18518513
申请日：2023-11-23
Applicant: University Of Electronic Science And Technology Of China , Yangtze Delta Region Institute (Huzhou), University Of Electronic Science And Technology Of China
Inventor： Shihua Li , Shunda Zhao , Yuyang Guo , Fugui Luo , Minfeng Xing
Abstract: Provided is an individual-tree segmentation method of UAV LiDAR point cloud based on canopy morphology. The method uses woodland data obtained by a UAV LiDAR to: extract initial canopies from a CHM based on a region growing algorithm, determine whether each initial canopy is a correct segmentation canopy according to the number of local density maximum points in each initial canopy, finely segment each wrong segmentation canopy according to canopy morphology to obtain an updated set of tree tops, and finally use each of the updated set of tree tops as a seed point for performing the region growing algorithm to thereby obtain a final individual-tree segmentation result. The method make full use of height information and density information contained in a tree point cloud; and under the guidance of the density information, a wrong segmentation tree can be more accurately identified.
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公开(公告)号：US12051211B2
公开(公告)日：2024-07-30
申请号：US17989453
申请日：2022-11-17
Applicant: University of Electronic Science and Technology of China , Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China
Inventor： Jiang Qian , Haitao Lyu , Junzheng Jiang , Minfeng Xing
CPC classification number: G06T7/20 , G06T2207/20081
Abstract: A moving target focusing method and system based on a generative adversarial network are provided. The method includes: generating, using a Range Doppler algorithm, a two-dimensional image including at least one defocused moving target, as a training sample; generating at least one ideal Gaussian point in a position of at least one center of the at least one defocused moving target in the two-dimensional image, to generate a training label; constructing the generative adversarial network, the generative adversarial network includes a generative network and a discrimination network; inputting the training sample and the training label into the generative adversarial network to perform repeated training until an output of the generative network reaches a preset condition, to thereby obtain a trained network model; and inputting a testing sample into the trained network model, to output a moving target focused image.
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公开(公告)号：US20220294605A1
公开(公告)日：2022-09-15
申请号：US17517661
申请日：2021-11-02
Applicant: University of Electronic Science and Technology of China , Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China
Inventor： Chunxiang XU , Changsong JIANG , Yicong DU
Abstract: A blockchain-based public parameter generation method against backdoor attacks, includes: acquiring the hash values of L latest confirmed blocks on a blockchain, and the hash values of the L blocks and a count variable for generation are mapped to an element in a set G via a specified mapping to obtain the generated public parameter; L≥φ, φ is the minimum number to guarantee blockchains' chain quality property; checking whether the generated parameter meets the condition, if not, discarding the parameter and updating the generated public parameter; if the condition is met, outputting the public parameter to the device that uses the public parameter. In this disclosure, the public parameters are random, since they are based on the latest confirmed blocks on the blockchain and are guaranteed by the computational power of the blockchain; the generation of public parameters is publicly verifiable and random.
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公开(公告)号：US20250020772A1
公开(公告)日：2025-01-16
申请号：US18517235
申请日：2023-11-22
Applicant: UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA , Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China
Inventor： Shihua Li , Ze He , Fugui Luo , Minfeng Xing
Abstract: A rice-crop intensity identification method based on radar time series observation and temperature analysis is provided. Capturing of diversified periodic characteristics of time series backscatter and detection of backscatter troughs are achieved through time series reconstruction and trough identification; potential phenological phases corresponding to the backscatter troughs are determined through potential rice phenological phase estimation; and through temperature limitation of rice phenological phase, temperature suitability of potential rice phenological phases is evaluated, a backscatter trough that does not satisfy a temperature condition is removed by combining a rice growth mechanism and a regulation of rice-crop intensity, thereby realizing the identification of the rice troughs and the correction of the overestimation of the rice-crop intensity, and finally realizing the identification of rice-crop intensity.
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公开(公告)号：US20230162373A1
公开(公告)日：2023-05-25
申请号：US17989453
申请日：2022-11-17
Applicant: University of Electronic Science and Technology of China , Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China
Inventor： Jiang Qian , Haitao Lyu , Junzheng Jiang , Minfeng Xing
IPC: G06T7/20
CPC classification number: G06T7/20 , G06T2207/20081
Abstract: A moving target focusing method and system based on a generative adversarial network are provided. The method includes: generating, using a Range Doppler algorithm, a two-dimensional image including at least one defocused moving target, as a training sample; generating at least one ideal Gaussian point in a position of at least one center of the at least one defocused moving target in the two-dimensional image, to generate a training label; constructing the generative adversarial network, the generative adversarial network includes a generative network and a discrimination network; inputting the training sample and the training label into the generative adversarial network to perform repeated training until an output of the generative network reaches a preset condition, to thereby obtain a trained network model; and inputting a testing sample into the trained network model, to output a moving target focused image.
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Patent Agency Ranking
公开(公告)号：US12300511B1
公开(公告)日：2025-05-13
申请号：US19021887
申请日：2025-01-15
Applicant: University of Electronic Science and Technology of China , Zhuhai YUEXIN Semiconductor Limited Liability Company
Inventor： Xianming Chen , Yuanming Chen , Lei Feng , Benxia Huang , Yongzhi Zeng , Wei He , Yanlin Dong
Abstract: In a fabrication method for a package structure, a copper foil is provided, electroplating is performed on the copper foil to form a cavity sacrificial post, a dielectric material is laminated to form a dielectric layer, wherein an end face of the cavity sacrificial post is exposed to the dielectric layer, a wiring layer is formed on the dielectric layer, the cavity sacrificial post is removed by etching to form a through cavity, a bonding pad is formed on the wiring layer, a reverse side of a device is mounted on the copper foil in the through cavity, and a terminal of the device is wire-bonded with the bonding pad.
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公开(公告)号：US12265109B2
公开(公告)日：2025-04-01
申请号：US18098704
申请日：2023-01-19
Inventor： Cheng Zeng , Tianhui Sun , Junsong Ning , Shirong Bu , Zhanping Wang
IPC: G01R27/26
Abstract: A device for measuring a microwave surface resistance of a dielectric conductor deposition interface includes: a test platform, a calibration component, a sealing cavity and a support plate; wherein the test platform comprises: a shielding cavity having an open bottom, a dielectric rod, an input coupling structure, an output coupling structure, and a dielectric supporter; the dielectric conductor test sample and the test platform form a TE0m(n+δ) mode dielectric resonator; the calibration component and the dielectric conductor test sample are mounted on the test platform to measure corresponding quality factors, thereby calculating the microwave surface resistance of the deposition interface of the dielectric conductor test sample. The present invention requires no pre-measurement of relative permittivity and loss tangent of the dielectric conductor test sample. After calibration, the microwave surface resistance of the dielectric conductor deposition interface can be obtained by only one non-destructive measurement.
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公开(公告)号：US12257571B2
公开(公告)日：2025-03-25
申请号：US17948794
申请日：2022-09-20
Applicant: Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China
Inventor： Jianping Sheng , Ye He , Guo Zhang , Fan Dong
Abstract: Disclosed is a method for preparing a bimetallic perovskite loaded grapheme-like carbon nitride photocatalyst, comprising: 11) dissolving SbCl3 and AgCl in HCl solution under heating and constant stirring; then adding CsCl in the heated solution to form sediment on the bottom of the beaker; collecting the sediment and wash it with ethanol, and finally drying in an oven to obtain Cs2AgSbCl6 powder; 12) adding melamine into an aluminum oxide crucible and placing it into a muffle furnace for calcination and finally cooling to room temperature naturally to obtain g-C3N4 samples; 13) adding the Cs2AgSbCl6 bimetallic perovskite and the g-C3N4 into a solvent, and stirring after subjecting to ultrasound, and drying after centrifuging to obtain the photocatalyst. Provided is a new idea for the combination of bimetallic halide perovskite and photocatalytic material, and the preparation method has mild conditions, simple operation, and is favorable for large-scale production.
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公开(公告)号：US20250094807A1
公开(公告)日：2025-03-20
申请号：US18384049
申请日：2023-10-26
Applicant: University of Electronic Science and Technology of China, Yangtze River Delta Research Institute
Inventor： Mei HE , Tianji XU , Pengpeng ZHI , Guangwei ZHANG , Jiao XUE , Yu ZHONG
IPC: G06N3/084
Abstract: Provided herein is a method and a system for data-driven prediction based on spatial information constraints, belonging to the technical field of intelligent information processing. The method comprises: prediction target interpolation based on collocated Co-Kriging; sample weight calculation based on sequential Gaussian simulation and loss function construction based on spatial information constraints; optimization of loss function and data-driven prediction based on deep fully connected neural network. The system comprises: data acquisition module, data preprocessing module, prediction target interpolation module, sample weight calculation module, loss function construction module, loss function optimization module, data-driven prediction module. It realizes the expansion of learning samples under the restriction of spatial information, and uses the spatial information to optimize the loss function, thus improving the utilization rate of data information, facilitating guiding the learning process to converge to reasonable assumptions, thereby improving the performance of the prediction method based on data-driven.
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10.发明申请公开(公告)号：US20250027808A1
公开(公告)日：2025-01-23
申请号：US18774967
申请日：2024-07-17
Inventor： Baicheng YAO , Xinyue HE , Bing CHANG , Teng TAN , Shangce WANG , Yu WU
IPC: G01H9/00
Abstract: Embodiments of the present disclosure relate to the field of acoustic sensing demodulation with high signal-to-noise ratio, real-time demodulation, and high sensitivity, and in particular, to a parallel sensing and demodulation system for acoustic waves based on dual optical frequency combs. The present disclosure introduces dual optical frequency combs as multi-path parallel input light sources, leveraging features of the dual optical frequency combs including narrow linewidth, stable power, high sensitivity, and the capability of precisely converting signals from the optical domain to the radio frequency domain, so the dual optical frequency combs can be used as multi-channel parallel input light sources for acoustic array detection. Besides, some embodiments of the present disclosure employ three-wavelength adaptive demodulation technology to ensure that the detection of acoustic wave signals at every moment has a high signal-to-noise ratio and improved sensitivity for detecting weak signals.
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