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公开(公告)号：US20230289940A1
公开(公告)日：2023-09-14
申请号：US17654687
申请日：2022-03-14
IPC分类号： G06T7/00
CPC分类号： G06T7/00 , G06T2207/10044 , G06T2207/30242 , G06T2207/20104
摘要： In an approach to improve detecting and identifying objects through orbital synthetic aperture radar satellites, embodiments arrange an array of elements in a predetermined configuration, and process, by a threshold and signature analysis, detected peaks in processed image data. Further, embodiments generate a list of objects detections based on the processed peaks, and identify an object based on amplitude, polarization ration, and polarization phase difference. Additionally, embodiments, classify the identified object based on the generated list of objects, and output, by a user interface, a list of probable object detections with position coordinates and identifications based on the classified identified objects, wherein the list of probable objects are above or within a predetermine threshold of confidence.
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公开(公告)号：US11119504B2
公开(公告)日：2021-09-14
申请号：US16184554
申请日：2018-11-08
发明人： Wang Zhou , Huan Hu , Wei Tan , Qianwen Chen
IPC分类号： G05D1/08 , G06N3/08 , B64D43/02 , G06K9/62 , G05D1/00 , G05D1/04 , G05D1/06 , G05D1/02 , B64C11/30 , G06N3/04
摘要： Using a set of airflow sensors disposed on an airfoil of an aircraft, first airflow data including an amount of airflow experienced at each airflow sensor at a first time is measured. Using a trained neural network model, the first airflow data is analyzed to determine an airflow state of the aircraft. In response to determining that the aircraft is in the abnormal airflow state, a control surface and a power unit of the aircraft are adjusted. Responsive to the adjusting, the aircraft is returned to the normal airflow state.
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公开(公告)号：US20210118117A1
公开(公告)日：2021-04-22
申请号：US16658533
申请日：2019-10-21
发明人： Conrad M. Albrecht , Hendrik F. Hamann , Levente Klein , Siyuan Lu , Sharathchandra Pankanti , Wang Zhou
摘要： Methods and systems for managing vegetation include training a machine learning model based on an image of a training data region before a weather event, an image of the training data region after the weather event, and information regarding the weather event. A risk score is generated for a second region using the trained machine learning model based on an image of the second region and predicted weather information for the second region. The risk score is determined to indicate high-risk vegetation in the second region. A corrective action is performed to reduce the risk of vegetation in the second region.
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公开(公告)号：US11594004B2
公开(公告)日：2023-02-28
申请号：US16727445
申请日：2019-12-26
发明人： Conrad M Albrecht , Ildar Khabibrakhmanov , Sharathchandra Pankanti , Levente Klein , Wang Zhou , Bruce Gordon Elmegreen , Siyuan Lu , Hendrik F Hamann , Carlo Siebenschuh
摘要： In some examples, a method of vector-raster data fusion includes receiving vector data for a geographical location, and statistically analyzing the vector data to obtain vector statistics. In some examples the method further includes rasterizing the vector statistics, and storing at least one of the vector data and the rasterized vector statistics together in a key-value store together with previously stored raster data for the geographical location. In some examples, the vector data further includes metadata, and the method further includes storing the metadata in at least one of the key-value store or a separate vector database.
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公开(公告)号：US11486857B2
公开(公告)日：2022-11-01
申请号：US17314634
申请日：2021-05-07
发明人： Oki Gunawan , Wang Zhou
IPC分类号： G01N27/72 , G01R33/07 , G01R33/032
摘要： Systems and methods are provided that facilitate high-sensitivity, carrier-resolved photo-Hall effect measurements. Majority and minority carrier properties can be measured and determined simultaneously. In one aspect, a system and method determine majority carrier type, density and mobility and, with modulated illumination, minority carrier mobility and photocarrier density. In another aspect, a system and method can determine hole and electron mobility, photocarrier density, absorbed photon density, recombination lifetime and diffusion length for hole, electron and ambipolar transport.
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公开(公告)号：US20210262982A1
公开(公告)日：2021-08-26
申请号：US17314634
申请日：2021-05-07
发明人： Oki Gunawan , Wang Zhou
IPC分类号： G01N27/72
摘要： Systems and methods are provided that facilitate high-sensitivity, carrier-resolved photo-Hall effect measurements. Majority and minority carrier properties can be measured and determined simultaneously. In one aspect, a system and method determine majority carrier type, density and mobility and, with modulated illumination, minority carrier mobility and photocarrier density. In another aspect, a system and method can determine hole and electron mobility, photocarrier density, absorbed photon density, recombination lifetime and diffusion length for hole, electron and ambipolar transport.
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公开(公告)号：US11163951B2
公开(公告)日：2021-11-02
申请号：US16729701
申请日：2019-12-30
发明人： Oki Gunawan , Lior Horesh , Giacomo Nannicini , Wang Zhou
IPC分类号： G06F40/253 , G06F16/33 , G06F40/211
摘要： A dimensionality analysis method, system, and computer program product, include conducting a search that determines which valid expressions in a data set satisfies a defined free-form grammar that describes the data set.
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公开(公告)号：US11080558B2
公开(公告)日：2021-08-03
申请号：US16360563
申请日：2019-03-21
发明人： Shiyu Chang , Emrah Akin Sisbot , Norma Edith Sosa , Wang Zhou
摘要： Methods and systems perform incremental learning object detection in images and/or videos without catastrophic forgetting of previously-learned object classes. A two-stage neural network object detector is trained to locate and identify objects pertaining to an additional object class by iteratively updating the two-stage neural network object detector until an overall detection accuracy criterion is met. The updating is performed so as to balance minimizing a loss of an initial ability to locate and identify objects pertaining to the previously-learned object classes and maximizing an ability to additionally locate and identify the objects pertaining to the additional object class. Assessing whether the overall detection accuracy criterion is met compares outputs of an initial version of the two-stage neural network object detector with a current region proposal output by a current version of the two-stage neural network object detector to determining a region proposal distillation loss and a previously-learned-object identification distillation loss.
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公开(公告)号：US20190354581A1
公开(公告)日：2019-11-21
申请号：US16527324
申请日：2019-07-31
发明人： Oki Gunawan , Lior Horesh , Giancomo Nannicini , Wang Zhou
摘要： A dimensionality analysis method, system, and computer program product, include defining a set of symbols along with a grammatical rule that define a syntax of a valid expression having a valid physical dimensionality relationship.
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公开(公告)号：US20190188236A1
公开(公告)日：2019-06-20
申请号：US15843234
申请日：2017-12-15
发明人： Lior Horesh , Giacomo Nannicini , Raya Horesh , Wang Zhou
CPC分类号： G06F17/13 , G06F17/5009 , G06F2217/16 , G06N20/00
摘要： Free-form discovery of differential equations for modeling a physical system or process under investigation that includes defining a formal language sentence grammar that describes admissible relationships between quantities, and incorporating the use of such grammar for free-(functional) form, automatic discovery of differential equations. The method requires minimum knowledge of the desired differential equation and is universally applicable to ordinary and partial differential equations. From received training set data representing inputs to the physical system and measured outputs, a numerical error bound data, primitive operators, differential equation operators, variables, coefficients and grammatical rules that define the syntax of valid expressions, the system finds a model characterized by sources of error to find a simplest (minimum complexity) mathematical expression comprising differential operators such that a discrepancy between the observed data and the value of the mathematical expression is bounded, and the mathematical expression is consistent with valid syntax constraints.
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