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公开(公告)号：US20170132497A1
公开(公告)日：2017-05-11
申请号：US15414433
申请日：2017-01-24
Applicant: Amazon Technologies, Inc.
Inventor： Anthony Alexander Santos , Adam James Finkelstein , David Akira Gingrich , David Michael Hurley , Siqi Zhao
CPC classification number: G06K9/66 , G06F17/30247 , G06F17/30256 , G06F17/3028 , G06K9/46 , G06K9/4628 , G06K9/6202 , G06K9/623 , G06K9/6282 , G06N3/04 , G06N3/0427 , G06N3/0454 , G06N3/08
Abstract: A system that identifies attributes of an item depicted in an image using artificial intelligence is provided. For example, the system may use one or more deep belief networks (DBNs) or convolution neural networks (CNNs) trained to analyze images and identify attributes in items depicted in the images. A first artificial intelligence module may analyze an image to determine a type of item depicted in the image. The system may then select a second artificial intelligence module that is associated with the type of item and use the second artificial intelligence module to identify attributes in the item depicted in the image. Identified attributes, if associated with a confidence level over a threshold value, may be provided to a user. The user may provide feedback on the accuracy of the identified attributes, which can be used to further train the first and/or second artificial intelligence modules.
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公开(公告)号：US09798960B2
公开(公告)日：2017-10-24
申请号：US15414433
申请日：2017-01-24
Applicant: Amazon Technologies, Inc.
Inventor： Anthony Alexander Santos , Adam James Finkelstein , David Akira Gingrich , David Michael Hurley , Siqi Zhao
CPC classification number: G06K9/66 , G06F17/30247 , G06F17/30256 , G06F17/3028 , G06K9/46 , G06K9/4628 , G06K9/6202 , G06K9/623 , G06K9/6282 , G06N3/04 , G06N3/0427 , G06N3/0454 , G06N3/08
Abstract: A system that identifies attributes of an item depicted in an image using artificial intelligence is provided. For example, the system may use one or more deep belief networks (DBNs) or convolution neural networks (CNNs) trained to analyze images and identify attributes in items depicted in the images. A first artificial intelligence module may analyze an image to determine a type of item depicted in the image. The system may then select a second artificial intelligence module that is associated with the type of item and use the second artificial intelligence module to identify attributes in the item depicted in the image. Identified attributes, if associated with a confidence level over a threshold value, may be provided to a user. The user may provide feedback on the accuracy of the identified attributes, which can be used to further train the first and/or second artificial intelligence modules.
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公开(公告)号：US09569700B1
公开(公告)日：2017-02-14
申请号：US14573892
申请日：2014-12-17
Applicant: Amazon Technologies, Inc.
Inventor： Anthony Alexander Santos , Adam James Finkelstein , David Akira Gingrich , David Michael Hurley , Siqi Zhao
CPC classification number: G06K9/66 , G06F17/30247 , G06F17/30256 , G06F17/3028 , G06K9/46 , G06K9/4628 , G06K9/6202 , G06K9/623 , G06K9/6282 , G06N3/04 , G06N3/0427 , G06N3/0454 , G06N3/08
Abstract: A system that identifies attributes of an item depicted in an image using artificial intelligence is provided. For example, the system may use one or more deep belief networks (DBNs) or convolution neural networks (CNNs) trained to analyze images and identify attributes in items depicted in the images. A first artificial intelligence module may analyze an image to determine a type of item depicted in the image. The system may then select a second artificial intelligence module that is associated with the type of item and use the second artificial intelligence module to identify attributes in the item depicted in the image. Identified attributes, if associated with a confidence level over a threshold value, may be provided to a user. The user may provide feedback on the accuracy of the identified attributes, which can be used to further train the first and/or second artificial intelligence modules.
Abstract translation: 提供了一种使用人工智能识别图像中描绘的项目的属性的系统。 例如，该系统可以使用经过训练的一个或多个深层信念网络（DBN）或卷积神经网络（CNN）来分析图像并识别图像中描绘的项目的属性。 第一人造智能模块可以分析图像以确定图像中描绘的项目的类型。 系统然后可以选择与项目类型相关联的第二人造智能模块，并使用第二人造智能模块来识别图像中描绘的项目中的属性。 如果与置信水平超过阈值相关联的标识属性可以被提供给用户。 用户可以提供关于所识别的属性的准确性的反馈，其可以用于进一步训练第一和/或第二人工智能模块。
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