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公开(公告)号：US09297918B2
公开(公告)日：2016-03-29
申请号：US13729769
申请日：2012-12-28
Applicant: General Electric Company
Inventor： Ser Nam Lim , John Robert Hare , Jens Rittscher , Jie Yu , Ya Xue
CPC classification number: G06N99/005 , G01V1/301 , G01V99/00 , G01V2210/64
Abstract: An approach for seismic data analysis is provided. In accordance with various embodiments, the active learning approaches are employed in conjunction with an analysis algorithm that is used to process the seismic data. Algorithms that may employ such active learning include, but are not limited to, ranking algorithms and classification algorithms.
Abstract translation: 提供了一种地震数据分析方法。 根据各种实施例，主动学习方法与用于处理地震数据的分析算法结合使用。 可以采用这种主动学习的算法包括但不限于排序算法和分类算法。
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Patent Agency Ranking
公开(公告)号：US20140188769A1
公开(公告)日：2014-07-03
申请号：US13729769
申请日：2012-12-28
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Ser Nam Lim , John Robert Hare , Jens Rittscher , Jie Yu , Ya Xue
IPC: G06N99/00
CPC classification number: G06N99/005 , G01V1/301 , G01V99/00 , G01V2210/64
Abstract: An approach for seismic data analysis is provided. In accordance with various embodiments, the active learning approaches are employed in conjunction with an analysis algorithm that is used to process the seismic data. Algorithms that may employ such active learning include, but are not limited to, ranking algorithms and classification algorithms.
Abstract translation: 提供了一种地震数据分析方法。 根据各种实施例，主动学习方法与用于处理地震数据的分析算法结合使用。 可以采用这种主动学习的算法包括但不限于排序算法和分类算法。
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公开(公告)号：US09477905B2
公开(公告)日：2016-10-25
申请号：US14798160
申请日：2015-07-13
Applicant: General Electric Company
Inventor： Xiaoming Liu , Peter Henry Tu , Ya Xue
CPC classification number: G06K9/6206 , G06K9/00281 , G06K9/6224 , G06K9/623 , G06K9/6263
Abstract: A novel technique for unsupervised feature selection is disclosed. The disclosed methods include automatically selecting a subset of a feature of an image. Additionally, the selection of the subset of features may be incorporated with a congealing algorithm, such as a least-square-based congealing algorithm. By selecting a subset of the feature representation of an image, redundant and/or irrelevant features may be reduced or removed, and the efficiency and accuracy of least-square-based congealing may be improved.
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公开(公告)号：US20150324663A1
公开(公告)日：2015-11-12
申请号：US14798160
申请日：2015-07-13
Applicant: General Electric Company
Inventor： Xiaoming Liu , Peter Henry Tu , Ya Xue
CPC classification number: G06K9/6206 , G06K9/00281 , G06K9/6224 , G06K9/623 , G06K9/6263
Abstract: A novel technique for unsupervised feature selection is disclosed. The disclosed methods include automatically selecting a subset of a feature of an image. Additionally, the selection of the subset of features may be incorporated with a congealing algorithm, such as a least-square-based congealing algorithm. By selecting a subset of the feature representation of an image, redundant and/or irrelevant features may be reduced or removed, and the efficiency and accuracy of least-square-based congealing may be improved.
Abstract translation: 公开了一种用于无监督特征选择的新技术。 所公开的方法包括自动选择图像的特征的子集。 另外，可以使用诸如基于最小二乘法的凝结算法的凝结算法来结合特征子集的选择。 通过选择图像的特征表示的子集，可以减少或去除冗余和/或不相关的特征，并且可以提高基于最小二乘法的凝结的效率和精度。
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公开(公告)号：US09082043B2
公开(公告)日：2015-07-14
申请号：US14323813
申请日：2014-07-03
Applicant: General Electric Company
Inventor： Xiaoming Liu , Peter Henry Tu , Ya Xue
CPC classification number: G06K9/6206 , G06K9/00281 , G06K9/6224 , G06K9/623 , G06K9/6263
Abstract: A novel technique for unsupervised feature selection is disclosed. The disclosed methods include automatically selecting a subset of a feature of an image. Additionally, the selection of the subset of features may be incorporated with a congealing algorithm, such as a least-square-based congealing algorithm. By selecting a subset of the feature representation of an image, redundant and/or irrelevant features may be reduced or removed, and the efficiency and accuracy of least-square-based congealing may be improved.
Abstract translation: 公开了一种用于无监督特征选择的新技术。 所公开的方法包括自动选择图像的特征的子集。 另外，可以使用诸如基于最小二乘法的凝结算法的凝结算法来结合特征子集的选择。 通过选择图像的特征表示的子集，可以减少或去除冗余和/或不相关的特征，并且可以提高基于最小二乘法的凝结的效率和精度。
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公开(公告)号：US20140321758A1
公开(公告)日：2014-10-30
申请号：US14323813
申请日：2014-07-03
Applicant: General Electric Company
Inventor： Xiaoming Liu , Peter Henry Tu , Ya Xue
IPC: G06K9/62
CPC classification number: G06K9/6206 , G06K9/00281 , G06K9/6224 , G06K9/623 , G06K9/6263
Abstract: A novel technique for unsupervised feature selection is disclosed. The disclosed methods include automatically selecting a subset of a feature of an image. Additionally, the selection of the subset of features may be incorporated with a congealing algorithm, such as a least-square-based congealing algorithm. By selecting a subset of the feature representation of an image, redundant and/or irrelevant features may be reduced or removed, and the efficiency and accuracy of least-square-based congealing may be improved.
Abstract translation: 公开了一种用于无监督特征选择的新技术。 所公开的方法包括自动选择图像的特征的子集。 另外，可以使用诸如基于最小二乘法的凝结算法的凝结算法来结合特征子集的选择。 通过选择图像的特征表示的子集，可以减少或去除冗余和/或不相关的特征，并且可以提高基于最小二乘法的凝结的效率和精度。
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