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公开(公告)号：US20190005334A1
公开(公告)日：2019-01-03
申请号：US16125045
申请日：2018-09-07
Applicant: Google LLC
Inventor： Matthias Grundmann , Alexandra Ivanna Hawkins , Sergey Ioffe
Abstract: Methods, systems, and media for summarizing a video with video thumbnails are provided. In some embodiments, the method comprises: receiving a plurality of video frames corresponding to the video and associated information associated with each of the plurality of video frames; extracting, for each of the plurality of video frames, a plurality of features; generating candidate clips that each includes at least a portion of the received video frames based on the extracted plurality of features and the associated information; calculating, for each candidate clip, a clip score based on the extracted plurality of features from the video frames associated with the candidate clip; calculating, between adjacent candidate clips, a transition score based at least in part on a comparison of video frame features between frames from the adjacent candidate clips; selecting a subset of the candidate clips based at least in part on the clip score and the transition score associated with each of the candidate clips; and automatically generating an animated video thumbnail corresponding to the video that includes a plurality of video frames selected from each of the subset of candidate clips.
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公开(公告)号：US10102443B1
公开(公告)日：2018-10-16
申请号：US15232941
申请日：2016-08-10
Applicant: Google LLC
Inventor： Qixing Huang , Mei Han , Bo Wu , Sergey Ioffe
Abstract: An image processing system automatically segments and labels an image using a hierarchical classification model. A global classification model determines initial labels for an image based on features of the image. A label-based descriptor is generated based on the initial labels. A local classification model is then selected from a plurality of learned local classification model based on the label-based descriptor. The local classification model is applied to the features of the input image to determined refined labels. The refined labels are stored in association with the input image.
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公开(公告)号：US10074015B1
公开(公告)日：2018-09-11
申请号：US15098024
申请日：2016-04-13
Applicant: Google LLC
Inventor： Matthias Grundmann , Alexandra Ivanna Hawkins , Sergey Ioffe
CPC classification number: G06K9/00765 , G06K9/00751 , G06K9/623
Abstract: Methods, systems, and media for summarizing a video with video thumbnails are provided. In some embodiments, the method comprises: receiving a plurality of video frames corresponding to the video and associated information associated with each of the plurality of video frames; extracting, for each of the plurality of video frames, a plurality of features; generating candidate clips that each includes at least a portion of the received video frames based on the extracted plurality of features and the associated information; calculating, for each candidate clip, a clip score based on the extracted plurality of features from the video frames associated with the candidate clip; calculating, between adjacent candidate clips, a transition score based at least in part on a comparison of video frame features between frames from the adjacent candidate clips; selecting a subset of the candidate clips based at least in part on the clip score and the transition score associated with each of the candidate clips; and automatically generating an animated video thumbnail corresponding to the video that includes a plurality of video frames selected from each of the subset of candidate clips.
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公开(公告)号：US11893485B2
公开(公告)日：2024-02-06
申请号：US17156453
申请日：2021-01-22
Applicant: Google LLC
Inventor： Sergey Ioffe , Corinna Cortes
CPC classification number: G06N3/08 , G06F18/10 , G06F18/2415 , G06N3/04 , G06N3/084 , G06V10/70 , G06V10/82 , G06T2207/20081
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using a neural network system that includes a batch normalization layer. One of the methods includes receiving a respective first layer output for each training example in the batch; computing a plurality of normalization statistics for the batch from the first layer outputs; normalizing each component of each first layer output using the normalization statistics to generate a respective normalized layer output for each training example in the batch; generating a respective batch normalization layer output for each of the training examples from the normalized layer outputs; and providing the batch normalization layer output as an input to the second neural network layer.
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公开(公告)号：US20220237462A1
公开(公告)日：2022-07-28
申请号：US17723007
申请日：2022-04-18
Applicant: Google LLC
Inventor： Sergey Ioffe , Corinna Cortes
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images or features of images using an image classification system that includes a batch normalization layer. One of the systems includes a convolutional neural network configured to receive an input comprising an image or image features of the image and to generate a network output that includes respective scores for each object category in a set of object categories, the score for each object category representing a likelihood that that the image contains an image of an object belonging to the category, and the convolutional neural network comprising: a plurality of neural network layers, the plurality of neural network layers comprising a first convolutional neural network layer and a second neural network layer; and a batch normalization layer between the first convolutional neural network layer and the second neural network layer.
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Patent Agency Ranking
公开(公告)号：US11308394B2
公开(公告)日：2022-04-19
申请号：US16837959
申请日：2020-04-01
Applicant: Google LLC
Inventor： Sergey Ioffe , Corinna Cortes
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing images or features of images using an image classification system that includes a batch normalization layer. One of the systems includes a convolutional neural network configured to receive an input comprising an image or image features of the image and to generate a network output that includes respective scores for each object category in a set of object categories, the score for each object category representing a likelihood that that the image contains an image of an object belonging to the category, and the convolutional neural network comprising: a plurality of neural network layers, the plurality of neural network layers comprising a first convolutional neural network layer and a second neural network layer; and a batch normalization layer between the first convolutional neural network layer and the second neural network layer.
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公开(公告)号：US20210357756A1
公开(公告)日：2021-11-18
申请号：US17390768
申请日：2021-07-30
Applicant: Google LLC
Inventor： Sergey Ioffe , Corinna Cortes
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using a neural network system that includes a batch normalization layer. One of the methods includes receiving a respective first layer output for each training example in the batch; computing a plurality of normalization statistics for the batch from the first layer outputs; normalizing each component of each first layer output using the normalization statistics to generate a respective normalized layer output for each training example in the batch; generating a respective batch normalization layer output for each of the training examples from the normalized layer outputs; and providing the batch normalization layer output as an input to the second neural network layer.
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公开(公告)号：US20210133565A1
公开(公告)日：2021-05-06
申请号：US16902547
申请日：2020-06-16
Applicant: Google LLC
Inventor： Gil Shamir , Dong Lin , Sergey Ioffe
Abstract: Aspects of the present disclosure are directed to novel activation functions which enable improved reproducibility and accuracy tradeoffs in neural networks. In particular, the present disclosure provides a family of activation functions that, on one hand, are smooth with continuous gradient and optionally monotonic but, on the other hand, also mimic the mathematical behavior of a Rectified Linear Unit (ReLU). As examples, the activation functions described herein include a smooth rectified linear unit function and also a leaky version of such function. In various implementations, the proposed functions can provide both a complete stop region and a constant positive gradient (e.g., that can be 1) pass region like a ReLU, thereby matching accuracy performance of a ReLU. Additional implementations include a leaky version and/or functions that feature different constant gradients in the pass region.
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公开(公告)号：US10902319B2
公开(公告)日：2021-01-26
申请号：US16572454
申请日：2019-09-16
Applicant: Google LLC
Inventor： Sergey Ioffe , Corinna Cortes
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing inputs using a neural network system that includes a batch normalization layer. One of the methods includes receiving a respective first layer output for each training example in the batch; computing a plurality of normalization statistics for the batch from the first layer outputs; normalizing each component of each first layer output using the normalization statistics to generate a respective normalized layer output for each training example in the batch; generating a respective batch normalization layer output for each of the training examples from the normalized layer outputs; and providing the batch normalization layer output as an input to the second neural network layer.
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公开(公告)号：US10521715B1
公开(公告)日：2019-12-31
申请号：US14997422
申请日：2016-01-15
Applicant: Google LLC
Inventor： Sergey Ioffe , Raymond Wensley Smith
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for implementing long-short term memory cells with saturating gating functions. One of the systems includes a first Long Short-Term Memory (LSTM) cell, wherein the first LSTM cell is configured to, for each of the plurality of time steps, generate a new cell state and a new cell output by applying a plurality of gates to a current cell input, a current cell state, and a current cell output, each of the plurality of gates being configured to, for each of the plurality of time steps: receive a gate input vector, generate a respective intermediate gate output vector from the gate input, and apply a respective gating function to each component of the respective intermediate gate output vector, wherein the respective gating function for at least one of the plurality of gates is a saturating gating function.
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