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公开(公告)号：US09165217B2
公开(公告)日：2015-10-20
申请号：US13744688
申请日：2013-01-18
Applicant: International Business Machines Corporation
Inventor： Liangliang Cao , Noel C. F. Codella , Gang Hua , John R. Smith
CPC classification number: G06K9/6256 , G06K9/00657
Abstract: Techniques for generating cross-modality semantic classifiers and using those cross-modality semantic classifiers for ground level photo geo-location using digital elevation are provided. In one aspect, a method for generating cross-modality semantic classifiers is provided. The method includes the steps of: (a) using Geographic Information Service (GIS) data to label satellite images; (b) using the satellite images labeled with the GIS data as training data to generate semantic classifiers for a satellite modality; (c) using the GIS data to label Global Positioning System (GPS) tagged ground level photos; (d) using the GPS tagged ground level photos labeled with the GIS data as training data to generate semantic classifiers for a ground level photo modality, wherein the semantic classifiers for the satellite modality and the ground level photo modality are the cross-modality semantic classifiers.
Abstract translation: 提供了用于生成交叉模态语义分类器的技术，并使用数字高程对地面照片地理位置使用这些交叉模式语义分类器。 一方面，提供了一种用于产生交叉模态语义分类器的方法。 该方法包括以下步骤：（a）使用地理信息服务（GIS）数据标记卫星图像; （b）使用标有GIS数据的卫星图像作为训练数据，生成卫星模式的语义分类器; （c）使用GIS数据标记全球定位系统（GPS）标记的地面照片; （d）使用标记有GIS数据的GPS标记的地面级照片作为训练数据，以生成用于地平面照片模式的语义分类器，其中用于卫星模态和地面照度模式的语义分类器是交叉模式语义分类器 。
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公开(公告)号：US11132618B2
公开(公告)日：2021-09-28
申请号：US15372821
申请日：2016-12-08
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Liangliang Cao , Ning Duan , Qian Lin , Chen Wang , Junchi Yan , Xin Zhang
Abstract: A method and apparatus for generating a training model based on feedback are provided. The method for generating a training model based on feedback, includes calculating an eigenvector of a sample among a plurality of samples; obtaining scores granted by a user for one or more of the plurality of samples in a round, obtaining scores granted by the user for a first number of samples; obtaining scores granted by the user for a second number of samples in response to detecting, based on the eigenvector, an inconsistency between the scores granted by the user for the first number of samples; and generating a training model based on the scores granted by the user for the first and second numbers of samples. A corresponding apparatus is also provided.
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公开(公告)号：US10346746B2
公开(公告)日：2019-07-09
申请号：US14055387
申请日：2013-10-16
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Liangliang Cao , Ning Duan , Qian Lin , Chen Wang , Junchi Yan , Xin Zhang
Abstract: A method and apparatus for generating a training model based on feedback are provided. The method for generating a training model based on feedback, includes calculating an eigenvector of a sample among a plurality of samples; obtaining scores granted by a user for one or more of the plurality of samples in a round, obtaining scores granted by the user for a first number of samples; obtaining scores granted by the user for a second number of samples in response to detecting, based on the eigenvector, an inconsistency between the scores granted by the user for the first number of samples; and generating a training model based on the scores granted by the user for the first and second numbers of samples. A corresponding apparatus is also provided.
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公开(公告)号：US09947073B2
公开(公告)日：2018-04-17
申请号：US15431986
申请日：2017-02-14
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Liangliang Cao , Liana L. Fong , Wei Tan
CPC classification number: G06T1/60 , G06F3/0601 , G06F3/0604 , G06F3/0659 , G06F3/0673 , G06F8/441 , G06F8/443 , G06F8/453 , G06F12/0813 , G06F12/0875 , G06F12/0877 , G06F13/16 , G06F17/16 , G06F2212/1024 , G06F2212/302 , G06F2212/454 , G06F2212/455 , G06F2212/60 , G06F2212/656 , H03M13/6566
Abstract: Embodiments include method, systems and computer program products for performing memory-aware matrix factorization on a graphics processing unit. Aspects include determining one or more types of memory on the graphics processing unit and determining one or more characteristics of each of the one or more types of memory. Aspects also include assigning each of a plurality of memory accesses of a matrix factorization algorithm to one of the one or more types of memory based on the one or more characteristics and executing the matrix factorization algorithm on the graphics processing unit.
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公开(公告)号：US09734166B2
公开(公告)日：2017-08-15
申请号：US13975497
申请日：2013-08-26
Applicant: International Business Machines Corporation
Inventor： Liangliang Cao , Yuan-Chi Chang , Quoc-Bao Nguyen
IPC: G06F17/30
CPC classification number: G06F17/30268 , G06F17/30017 , G06F17/30038 , G06F17/30855
Abstract: A first set of contextual dimensions is generated from one or more textual descriptions associated with a given event, which includes one or more examples. A second set of contextual dimensions is generated from one or more visual features associated with the given event, which includes one or more visual example recordings. A similarity structure is constructed from the first set of contextual dimensions and the second set of contextual dimensions. One or more of the textual descriptions is matched with one or more of the visual features based on the similarity structure.
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Patent Agency Ranking
公开(公告)号：US20170162189A1
公开(公告)日：2017-06-08
申请号：US15437490
申请日：2017-02-21
Applicant: International Business Machines Corporation
Inventor： Liangliang Cao , James J. Fan , Chang Wang , Bing Xiang , Bowen Zhou
CPC classification number: G10L15/063 , G06F17/241 , G06F17/28 , G06F17/3069 , G06N3/04 , G06N3/08 , G06N3/084 , G06N3/088 , G06N5/022 , G06N99/005 , G10L15/16 , G10L15/18
Abstract: Software that trains an artificial neural network for generating vector representations for natural language text, by performing the following steps: (i) receiving, by one or more processors, a set of natural language text; (ii) generating, by one or more processors, a set of first metadata for the set of natural language text, where the first metadata is generated using supervised learning method(s); (iii) generating, by one or more processors, a set of second metadata for the set of natural language text, where the second metadata is generated using unsupervised learning method(s); and (iv) training, by one or more processors, an artificial neural network adapted to generate vector representations for natural language text, where the training is based, at least in part, on the received natural language text, the generated set of first metadata, and the generated set of second metadata.
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公开(公告)号：US09659560B2
公开(公告)日：2017-05-23
申请号：US14870204
申请日：2015-09-30
Applicant: International Business Machines Corporation
Inventor： Liangliang Cao , James J. Fan , Chang Wang , Bing Xiang , Bowen Zhou
IPC: G06F17/27 , G06F17/21 , G10L15/00 , G10L15/06 , G10L15/18 , G10L15/16 , G06F17/28 , G06N3/04 , G06N99/00 , G06F17/30
CPC classification number: G10L15/063 , G06F17/241 , G06F17/28 , G06F17/3069 , G06N3/04 , G06N3/08 , G06N3/084 , G06N3/088 , G06N5/022 , G06N99/005 , G10L15/16 , G10L15/18
Abstract: Software that trains an artificial neural network for generating vector representations for natural language text, by performing the following steps: (i) receiving, by one or more processors, a set of natural language text; (ii) generating, by one or more processors, a set of first metadata for the set of natural language text, where the first metadata is generated using supervised learning method(s); (iii) generating, by one or more processors, a set of second metadata for the set of natural language text, where the second metadata is generated using unsupervised learning method(s); and (iv) training, by one or more processors, an artificial neural network adapted to generate vector representations for natural language text, where the training is based, at least in part, on the received natural language text, the generated set of first metadata, and the generated set of second metadata.
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公开(公告)号：US20160328388A1
公开(公告)日：2016-11-10
申请号：US14870204
申请日：2015-09-30
Applicant: International Business Machines Corporation
Inventor： Liangliang Cao , James J. Fan , Chang Wang , Bing Xiang , Bowen Zhou
CPC classification number: G10L15/063 , G06F17/241 , G06F17/28 , G06F17/3069 , G06N3/04 , G06N3/08 , G06N3/084 , G06N3/088 , G06N5/022 , G06N99/005 , G10L15/16 , G10L15/18
Abstract: Software that trains an artificial neural network for generating vector representations for natural language text, by performing the following steps: (i) receiving, by one or more processors, a set of natural language text; (ii) generating, by one or more processors, a set of first metadata for the set of natural language text, where the first metadata is generated using supervised learning method(s); (iii) generating, by one or more processors, a set of second metadata for the set of natural language text, where the second metadata is generated using unsupervised learning method(s); and (iv) training, by one or more processors, an artificial neural network adapted to generate vector representations for natural language text, where the training is based, at least in part, on the received natural language text, the generated set of first metadata, and the generated set of second metadata.
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29.发明授权公开(公告)号：US09471851B1
公开(公告)日：2016-10-18
申请号：US14754012
申请日：2015-06-29
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Liangliang Cao , Michele Merler , John R. Smith
CPC classification number: G06K9/628 , G06F17/2785 , G06K9/00288 , G06K9/00302 , G06K9/00362 , G06K9/00677 , G06K9/325 , G06K9/6293 , G06N5/04 , G06N7/005
Abstract: A method and systems are provided. The method includes recognizing semantic concepts in a set of images and assigning semantic scores for the images to predict a gender of a user. The method further includes performing gender prediction from visual content and textual content in the images to respectively generate visual-based gender predictions and textual-based gender predictions. The method also includes combining, using multimodal information fusion, the visual-based gender predictions, the textual-based gender predictions, and the semantic scores, to infer a gender of a user.
Abstract translation: 提供了一种方法和系统。 该方法包括识别一组图像中的语义概念，并为图像分配语义分数以预测用户的性别。 该方法还包括从图像中的视觉内容和文本内容执行性别预测，以分别产生基于视觉的性别预测和基于文本的性别预测。 该方法还包括结合使用多模态信息融合，基于视觉的性别预测，基于文本的性别预测和语义分数来推断用户的性别。
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公开(公告)号：US20150074021A1
公开(公告)日：2015-03-12
申请号：US14025208
申请日：2013-09-12
Applicant: International Business Machines Corporation
Inventor： Liangliang Cao , Ning Duan , Qian Lin , Chen Wang , Junchi Yan , Xin Zhang
CPC classification number: G06N3/08 , G06F12/06 , G06F17/30038 , G06N3/088 , G06N5/02 , G06N5/025 , G06N7/023 , G06N99/005 , G06Q30/02
Abstract: A method and apparatus for generating a training model based on feedback are provided. The method for generating a training model based on feedback, includes calculating an eigenvector of a sample among a plurality of samples; obtaining scores granted by a user for one or more of the plurality of samples in a round, obtaining scores granted by the user for a first number of samples; obtaining scores granted by the user for a second number of samples in response to detecting, based on the eigenvector, an inconsistency between the scores granted by the user for the first number of samples; and generating a training model based on the scores granted by the user for the first and second numbers of samples. A corresponding apparatus is also provided.
Abstract translation: 提供了一种基于反馈产生训练模型的方法和装置。 基于反馈生成训练模型的方法包括计算多个样本中的样本的特征向量; 获得由用户为一个或多个所述多个样本在一轮中授予的分数，获得由用户为第一数量的样本授予的分数; 响应于基于特征向量检测用户对于第一数量样本的分数的不一致性，获得用户对于第二数量样本所授予的分数; 以及基于用户为第一和第二数量样本授予的分数生成训练模型。 还提供了相应的装置。
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