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11.发明申请公开(公告)号：US20180107660A1
公开(公告)日：2018-04-19
申请号：US14316905
申请日：2014-06-27
Applicant: Amazon Technologies, Inc.
Inventor： Meng Wang , Yushan Chen
IPC: G06F17/30
CPC classification number: G06F16/51 , G06F16/10 , G06F16/284 , G06F16/58 , G06F16/5854
Abstract: An image organizing system for organizing and retrieving images from an image repository residing on a mobile device is disclosed. The image organizing system includes a mobile computing device including an image repository. The mobile computing device is adapted to produce a small-scale model from an image in the image repository including an indicia of the image from which the small-scale model was produced. In one embodiment the small-scale model is then transmitted from the mobile computing device to a cloud computing platform including recognition software that produces a list of tags describing the image, which are then transmitted back to the mobile computing device. The tags then form an organization system. Alternatively, the image recognition software can reside on the mobile computing device, so that no cloud computing platform is required.
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公开(公告)号：US10242034B1
公开(公告)日：2019-03-26
申请号：US14980775
申请日：2015-12-28
Applicant: Amazon Technologies, Inc.
Inventor： Yi Li , Yuxin Wu , Yushan Chen , Meng Wang
Abstract: Images are intelligently selected to create image narratives. Instead of a user having to manually search and locate images to view, the images to associate with a particular image narrative are programmatically determined. Many different types of image narratives may be created. For example, one image narrative may show images that include both a first user and a second user over some period of time. Another image narrative may show images that relate to an activity that a first user enjoys or an event that included the user (e.g., a graduation). The tags and metadata associated with the images of the user are analyzed to determine the tags that are important to the user. For example, the importance might be determined based on the frequency of the tags within the images. After creation, the user may select one of the image narratives to view the associated images.
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公开(公告)号：US09792530B1
公开(公告)日：2017-10-17
申请号：US14980898
申请日：2015-12-28
Applicant: Amazon Technologies, Inc.
CPC classification number: G06K9/6253 , G06K9/46 , G06K9/6267 , G06N3/0427 , G06N3/084
Abstract: A knowledge base (KB) is generated and used to classify images. The knowledge base includes a number subcategories of a specified category. Instead of obtaining images just based on a category name, structured and unstructured data sources are used to identify subcategories of the category. Subcategories that are determined to not be relevant to the category may be removed. The remaining data may be used to generate the KB. After identifying the relevant subcategories, representative images are obtained from one or more image sources based on the subcategories identified by the KB. The obtained images and the KB are then used to train an image classifier, such as a neural network or some other machine learning mechanism. After training, the neural network might, for example, classify an object within an image of a car, as a car, but also as a particular brand and model type.
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公开(公告)号：US11836160B1
公开(公告)日：2023-12-05
申请号：US15902686
申请日：2018-02-22
Applicant: Amazon Technologies, Inc.
CPC classification number: G06F16/285 , G06F18/24 , G06N3/08 , G06N20/00 , G06T7/73 , G06N3/04 , G06T2207/20081 , G06T2207/20084
Abstract: Techniques for user customized private label prediction are described. According to some embodiments, customers can train a classifier to detect new objects in image data. These new objects may not be included in a base model provided by a service provider system. The base model can be utilized to perform object detection and feature extraction from training images that are annotated by the customer to identify the new objects. Once trained, the new custom model can be used to identify the new objects in input images and label the images accordingly.
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公开(公告)号：US11501573B1
公开(公告)日：2022-11-15
申请号：US16894709
申请日：2020-06-05
Applicant: Amazon Technologies, Inc.
Inventor： Joseph P. Tighe , Meng Wang , Hao Wu , Manchen Wang
Abstract: Personal equipment detection may utilize pose-based detection. Input image data may be evaluated to detect persons in the image data. For detected persons, regions of the persons may be determined. Personal equipment may be detected for the detected persons in the image data and compared with the regions of the persons to determine whether the detected personal equipment is properly placed on the person.
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Patent Agency Ranking
公开(公告)号：US10652565B1
公开(公告)日：2020-05-12
申请号：US15782725
申请日：2017-10-12
Applicant: Amazon Technologies, inc.
Inventor： Jia Bi Zhang , Andrea Olgiati , Meng Wang
IPC: H04N19/463 , G06K9/62 , G06T9/00 , G06N20/00
Abstract: A processing device receives a representation of an image, wherein the image has a first size and the representation has a second size that is smaller than the first size, the representation having been generated from the image by a first portion of a first trained machine learning model. The processing device processes the representation of the image using a second portion of the trained machine learning model to generate a reconstruction of the image and then outputs the reconstruction of the image.
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公开(公告)号：US20190220483A1
公开(公告)日：2019-07-18
申请号：US16363955
申请日：2019-03-25
Applicant: Amazon Technologies, Inc.
Inventor： Yi Li , Yuxin Wu , Yushan Chen , Meng Wang
IPC: G06F16/58 , G06K9/00 , G06F16/9535
CPC classification number: G06F16/5866 , G06F16/4393 , G06F16/9535 , G06K9/00288
Abstract: Images are intelligently selected to create image narratives. Instead of a user having to manually search and locate images to view, the images to associate with a particular image narrative are programmatically determined. Many different types of image narratives may be created. For example, one image narrative may show images that include both a first user and a second user over some period of time. Another image narrative may show images that relate to an activity that a first user enjoys or an event that included the user (e.g., a graduation). The tags and metadata associated with the images of the user are analyzed to determine the tags that are important to the user. For example, the importance might be determined based on the frequency of the tags within the images. After creation, the user may select one of the image narratives to view the associated images.
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公开(公告)号：US11475684B1
公开(公告)日：2022-10-18
申请号：US16830148
申请日：2020-03-25
Applicant: Amazon Technologies, Inc.
Abstract: An image may be evaluated by a computer vision system to determine whether it is fit for analysis. The computer vision system may generate an embedding of the image. An embedding quality score (EQS) of the image may be determined based on the image's embedding and a reference embedding associated with a cluster of reference noisy images. The quality of the image may be evaluated based on the EQS of the image to determine whether the quality meets filter criteria. The image may be further processed when the quality is sufficient, or otherwise the image may be removed.
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公开(公告)号：US11272164B1
公开(公告)日：2022-03-08
申请号：US16746313
申请日：2020-01-17
Applicant: Amazon Technologies, Inc.
Inventor： Yifan Xing , Yuanjun Xiong , Wei Xia , Wei Li , Shuo Yang , Meng Wang
IPC: H04N13/275 , G06T7/73 , G06N20/00 , G06T15/50
Abstract: Techniques for data synthesis for training datasets for machine learning applications are described. A first image of at least an object from a first viewpoint is obtained. The first image having associated first image metadata including a first location of a feature of the object in the first image. A model is generated from the first image, the model including a three-dimensional representation of the object. A second image is generated from the model, the second image including the object from a second viewpoint that is different from the first viewpoint. Second image metadata is generated, the second image metadata including a second location of the feature of the object in the second image, the second location corresponding to the first location adjusted for the difference between the second viewpoint and the first viewpoint.
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公开(公告)号：US11080316B1
公开(公告)日：2021-08-03
申请号：US15607199
申请日：2017-05-26
Applicant: Amazon Technologies, Inc.
Inventor： Ranju Das , Wei Xia , Meng Wang , Xiaofeng Ren
IPC: G06F16/33 , G06F16/335 , G06F16/16 , G06F16/432
Abstract: People represented in multiple images can be recognized using accurate facial similarity metrics, where the accuracy can be further improved using contextual information. A set of models can be trained to process image data, and facial features can be extracted from a face region of an image and passed to the trained models. Resulting feature vectors can be concatenated and the dimensionality reduced to generate a highly accurate feature vector that is representative of the face in the image. The feature vector can be used to locate similar vectors in a multi-dimensional vector space, where similarity can be determined based at least in part upon the distance between the endpoints of those vectors in the vector space. Context information from the image can be used to adjust the similarity determination. Similar vectors can be clustered together such that the faces represented by those images are associated with the same person.
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