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公开(公告)号:US20240330361A1
公开(公告)日:2024-10-03
申请号:US18741082
申请日:2024-06-12
Applicant: Google LLC
Inventor: Zhen Li , Yi-Ting Chen , Yaxi Gao , Da-Cheng Juan , Aleksei Timofeev , Chun-Ta Lu , Futang Peng , Sujith Ravi , Andrew Tomkins , Thomas J. Duerig
IPC: G06F16/55 , G06F16/538 , G06F16/9538 , G06F18/214 , G06F18/22 , G06F18/40 , G06N3/042 , G06N3/044 , G06N3/084
CPC classification number: G06F16/55 , G06F16/538 , G06F16/9538 , G06F18/2148 , G06F18/22 , G06F18/41 , G06N3/042 , G06N3/044 , G06N3/084
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image embedding model. In one aspect, a method comprises: obtaining training data comprising a plurality of training examples, wherein each training example comprises: an image pair comprising a first image and a second image; and selection data indicating one or more of: (i) a co-click rate of the image pair, and (ii) a similar-image click rate of the image pair; and using the training data to train an image embedding model having a plurality of image embedding model parameters.
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公开(公告)号:US20230205813A1
公开(公告)日:2023-06-29
申请号:US18171511
申请日:2023-02-20
Applicant: Google LLC
Inventor: Zhen Li , Yi-Ting Chen , Yaxi Gao , Da-Cheng Juan , Aleksei Timofeev , Chun-Ta Lu , Futang Peng , Sujith Ravi , Andrew Tomkins , Thomas J. Duerig
IPC: G06F16/55 , G06F16/538 , G06F16/9538 , G06N3/084 , G06F18/22 , G06F18/40 , G06F18/214 , G06N3/042 , G06N3/044
CPC classification number: G06F16/55 , G06F16/538 , G06F16/9538 , G06N3/084 , G06F18/22 , G06F18/41 , G06F18/2148 , G06N3/042 , G06N3/044
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image embedding model. In one aspect, a method comprises: obtaining training data comprising a plurality of training examples, wherein each training example comprises: an image pair comprising a first image and a second image; and selection data indicating one or more of: (i) a co-click rate of the image pair, and (ii) a similar-image click rate of the image pair; and using the training data to train an image embedding model having a plurality of image embedding model parameters.
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公开(公告)号:US20240370487A1
公开(公告)日:2024-11-07
申请号:US18253859
申请日:2022-11-04
Applicant: Google LLC
Inventor: Severin Heiniger , Balint Miklos , Yun-Hsuan Sung , Zhen Li , Yinfei Yang , Chao Jia
IPC: G06F16/538 , G06F16/55 , G06N3/084
Abstract: Systems and methods of the present disclosure are directed to computer-implemented method for machine-learned multimodal search refinement. The method includes obtaining a query image embedding for a query image and a textual query refinement associated with the query image. The method includes processing the query image embedding and the textual query refinement with a machine-learned query refinement model to obtain a refined query image embedding that incorporates the textual query refinement. The method includes evaluating a loss function that evaluates a distance between the refined query image embedding and an embedding for a ground truth image within an image embedding space. The method includes modifying value(s) of parameter(s) of the machine-learned query refinement model based on the loss function.
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公开(公告)号:US20240078258A1
公开(公告)日:2024-03-07
申请号:US18505776
申请日:2023-11-09
Applicant: Google LLC
Inventor: Zhen Li , Yi-ting Chen , Ning Ye , Yaxi Gao , Zijian Guo , Aleksei Timofeev , Futang Peng , Thomas J. Duerig
IPC: G06F16/55 , G06F16/242 , G06F16/953 , G06F18/22 , G06N3/044 , G06N3/084 , G06N20/00
CPC classification number: G06F16/55 , G06F16/2425 , G06F16/953 , G06F18/22 , G06N3/044 , G06N3/084 , G06N20/00
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an image embedding model and a text embedding model. In one aspect, a method comprises: processing data from a historical query log of a search system to generate a candidate set of training examples, wherein each training example comprises: (i) a search query comprising a sequence of one or more words, (ii) an image, and (iii) selection data characterizing how often users selected the image in response to the image being identified by a search result for the search query; selecting a plurality of training examples from the candidate set of training examples; and using the training data to jointly train the image embedding model and the text embedding model.
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公开(公告)号:US11907337B2
公开(公告)日:2024-02-20
申请号:US17046313
申请日:2019-11-18
Applicant: Google LLC
Inventor: Ariel Fuxman , Aleksei Timofeev , Zhen Li , Chun-Ta Lu , Manan Shah , Chen Sun , Krishnamurthy Viswanathan , Chao Jia
IPC: G06K9/62 , G06K9/46 , G06F18/24 , G06F18/214 , G06F18/2413
CPC classification number: G06F18/24 , G06F18/214 , G06F18/24147
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for realizing a multimodal image classifier. In an aspect, a method includes, for each image of a plurality of images: processing the image by a textual generator model to obtain a set of phrases that are descriptive of the content of the image, wherein each phrase is one or more terms, processing the set of phrases by a textual embedding model to obtain an embedding of predicted text for the image, and processing the image using an image embedding model to obtain an embedding of image pixels of the image. Then a multimodal image classifier is trained on the embeddings of predicted text for the images and the embeddings of image pixels for the images to produce, as output, labels of an output taxonomy to classify an image based on the image as input.
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公开(公告)号:US12038970B2
公开(公告)日:2024-07-16
申请号:US18171511
申请日:2023-02-20
Applicant: Google LLC
Inventor: Zhen Li , Yi-Ting Chen , Yaxi Gao , Da-Cheng Juan , Aleksei Timofeev , Chun-Ta Lu , Futang Peng , Sujith Ravi , Andrew Tomkins , Thomas J. Duerig
IPC: G06F16/00 , G06F16/538 , G06F16/55 , G06F16/9538 , G06F18/214 , G06F18/22 , G06F18/40 , G06N3/042 , G06N3/044 , G06N3/084
CPC classification number: G06F16/55 , G06F16/538 , G06F16/9538 , G06F18/2148 , G06F18/22 , G06F18/41 , G06N3/042 , G06N3/044 , G06N3/084
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image embedding model. In one aspect, a method comprises: obtaining training data comprising a plurality of training examples, wherein each training example comprises: an image pair comprising a first image and a second image; and selection data indicating one or more of: (i) a co-click rate of the image pair, and (ii) a similar-image click rate of the image pair; and using the training data to train an image embedding model having a plurality of image embedding model parameters.
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公开(公告)号:US12008057B2
公开(公告)日:2024-06-11
申请号:US17509767
申请日:2021-10-25
Applicant: Google LLC
Inventor: Kristina Bohl , Ivan Oropeza , Lily Berg , Tracy Gu , Ethan Schreiber , Shanfeng Zhang , Howard Zhou , David Hendon , Zhen Li , Futang Peng , Teresa Ko , Jason Chang
IPC: G06F16/9535 , G06F16/906 , G06F16/9538 , G06F40/30 , G06N20/00
CPC classification number: G06F16/9535 , G06F16/906 , G06F16/9538 , G06F40/30 , G06N20/00
Abstract: A media application determines, based on pixels of images or videos from a collection of media items, clusters of media items such that the media items in each cluster have a visual similarity, wherein the collection of media items is associated with a user account. The media application selects a subset of the clusters of media from corresponding clusters of media items based on the media items in each cluster having a visual similarity within a range of threshold similarity values. The media application causes a user interface to be displayed that includes the subset of the clusters of media.
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公开(公告)号:US20210264203A1
公开(公告)日:2021-08-26
申请号:US17046313
申请日:2019-11-18
Applicant: Google LLC
Inventor: Ariel Fuxman , Aleksei Timofeev , Zhen Li , Chun-Ta Lu , Manan Shah , Chen Sun , Krishnamurthy Viswanathan , Chao Jia
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for realizing a multimodal image classifier. In an aspect, a method includes, for each image of a plurality of images: processing the image by a textual generator model to obtain a set of phrases that are descriptive of the content of the image, wherein each phrase is one or more terms, processing the set of phrases by a textual embedding model to obtain an embedding of predicted text for the image, and processing the image using an image embedding model to obtain an embedding of image pixels of the image. Then a multimodal image classifier is trained on the embeddings of predicted text for the images and the embeddings of image pixels for the images to produce, as output, labels of an output taxonomy to classify an image based on the image as input.
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公开(公告)号:US20200250538A1
公开(公告)日:2020-08-06
申请号:US16265811
申请日:2019-02-01
Applicant: Google LLC
Inventor: Zhen Li , Yi-ting Chen , Ning Ye , Yaxi Gao , Zijian Guo , Aleksei Timofeev , Futang Peng , Thomas J. Duerig
IPC: G06N3/08 , G06K9/62 , G06F16/953 , G06F16/242 , G06N20/00 , G06N3/04
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an image embedding model and a text embedding model. In one aspect, a method comprises: processing data from a historical query log of a search system to generate a candidate set of training examples, wherein each training example comprises: (i) a search query comprising a sequence of one or more words, (ii) an image, and (iii) selection data characterizing how often users selected the image in response to the image being identified by a search result for the search query; selecting a plurality of training examples from the candidate set of training examples; and using the training data to jointly train the image embedding model and the text embedding model.
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公开(公告)号:US20240143700A1
公开(公告)日:2024-05-02
申请号:US18409411
申请日:2024-01-10
Applicant: Google LLC
Inventor: Ariel Fuxman , Aleksei Timofeev , Zhen Li , Chun-Ta Lu , Manan Shah , Chen Sun , Krishnamurthy Viswanathan , Chao Jia
IPC: G06F18/24 , G06F18/214 , G06F18/2413
CPC classification number: G06F18/24 , G06F18/214 , G06F18/24147
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for realizing a multimodal image classifier. In an aspect, a method includes, for each image of a plurality of images: processing the image by a textual generator model to obtain a set of phrases that are descriptive of the content of the image, wherein each phrase is one or more terms, processing the set of phrases by a textual embedding model to obtain an embedding of predicted text for the image, and processing the image using an image embedding model to obtain an embedding of image pixels of the image. Then a multimodal image classifier is trained on the embeddings of predicted text for the images and the embeddings of image pixels for the images to produce, as output, labels of an output taxonomy to classify an image based on the image as input.
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