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公开(公告)号:US20210073617A1
公开(公告)日:2021-03-11
申请号:US16567277
申请日:2019-09-11
Applicant: Amazon Technologies, Inc.
Inventor: Loris Bazzani , Maksim Lapin , Felix Hieber , Tobias Domhan
Abstract: Techniques are generally described for automatic scoring of alt-text for image data. In various examples, first image data and first text data describing the first image data may be received. A feature representation of the first image data may be determined using an encoder machine learning model. A hidden state representation may be determined using a decoder machine learning model based on the feature representation and a first word of the first text data. In some examples, a first score may be determined using the hidden state representation. The first score may include an indication of a descriptive capability of the first text data with respect to the first image data.
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公开(公告)号:US11361212B2
公开(公告)日:2022-06-14
申请号:US16567277
申请日:2019-09-11
Applicant: Amazon Technologies, Inc.
Inventor: Loris Bazzani , Maksim Lapin , Felix Hieber , Tobias Domhan
Abstract: Techniques are generally described for automatic scoring of alt-text for image data. In various examples, first image data and first text data describing the first image data may be received. A feature representation of the first image data may be determined using an encoder machine learning model. A hidden state representation may be determined using a decoder machine learning model based on the feature representation and a first word of the first text data. In some examples, a first score may be determined using the hidden state representation. The first score may include an indication of a descriptive capability of the first text data with respect to the first image data.
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公开(公告)号:US11853390B1
公开(公告)日:2023-12-26
申请号:US16054709
申请日:2018-08-03
Applicant: Amazon Technologies, Inc.
Inventor: Bradley Scott Bowman , Maksim Lapin , Leo Parker Dirac
IPC: G06N3/08 , G06F18/2135 , G06N3/04 , G06N20/00 , G06F16/904 , G06F18/21
CPC classification number: G06F18/2135 , G06F16/904 , G06F18/217 , G06N3/04 , G06N3/08 , G06N20/00
Abstract: Techniques for evaluating an output of a machine learning model and using the evaluation to retrain the machine learning model are described. For example, a data set that is output from a layer of the machine learning model is reduced to a 2-D or 3-D representation that is suitable for viewing. A user views the reduced data set in a viewing environment such as virtual reality or augmented reality. The user makes changes using that viewing environment. The changes are then used to retrain the machine learning model.
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