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    Multimodal Image Classifier using Textual and Visual Embeddings
    5.
    发明公开
    Multimodal Image Classifier using Textual and Visual Embeddings 审中-公开

    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.

    Multimodal Image Classifier using Textual and Visual Embeddings
    9.
    发明申请
    Multimodal Image Classifier using Textual and Visual Embeddings 有权

    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

    IPC: G06K9/62 ,  G06K9/46

    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.

    TRAINING IMAGE AND TEXT EMBEDDING MODELS
    10.
    发明申请
    TRAINING IMAGE AND TEXT EMBEDDING MODELS 审中-公开

    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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