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1.发明授权公开(公告)号：US10198832B2
公开(公告)日：2019-02-05
申请号：US16022170
申请日：2018-06-28
Applicant: DeepMind Technologies Limited
Inventor： Jeffrey De Fauw , Joseph R. Ledsam , Bernardino Romera-Paredes , Stanislav Nikolov , Nenad Tomasev , Samuel Blackwell , Harry Askham , Xavier Glorot , Balaji Lakshminarayanan , Trevor Back , Mustafa Suleyman , Pearse A. Keane , Olaf Ronneberger , Julien Robert Michel Cornebise
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final classification output for an image of eye tissue. The image is provided as input to each of one or more segmentation neural networks to obtain one or more segmentation maps of the eye tissue in the image. A respective classification input is generated from each of the segmentation maps. For each of the segmentation maps, the classification input for the segmentation map is provided as input to each of one or more classification neural networks to obtain, for each segmentation map, a respective classification output from each classification neural network. A final classification output for the image is generated from the respective classification outputs for each of the segmentation maps.
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Patent Agency Ranking
2.发明申请公开(公告)号：US20200082534A1
公开(公告)日：2020-03-12
申请号：US16565384
申请日：2019-09-09
Applicant: DeepMind Technologies Limited
Inventor： Stanislav Nikolov , Samuel Blackwell , Jeffrey De Fauw , Bernardino Romera-Paredes , Clemens Meyer , Harry Askham , Cian Hughes , Trevor Back , Joseph R. Ledsam , Olaf Ronneberger
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for segmenting a medical image. In one aspect, a method comprises: receiving a medical image that is captured using a medical imaging modality and that depicts a region of tissue in a body; and processing the medical image using a segmentation neural network to generate a segmentation output, wherein the segmentation neural network comprises a sequence of multiple encoder blocks, wherein: each encoder block is a residual neural network block comprising one or more two-dimensional convolutional neural network layers, one or more three-dimensional convolutional neural network layers, or both, and each encoder block is configured to process a respective encoder block input to generate a respective encoder block output wherein a spatial resolution of the encoder block output is lower than a spatial resolution of the encoder block input.
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3.发明申请公开(公告)号：US20190139270A1
公开(公告)日：2019-05-09
申请号：US16236045
申请日：2018-12-28
Applicant: DeepMind Technologies Limited
Inventor： Jeffrey De Fauw , Joseph R. Ledsam , Bernardino Romera-Paredes , Stanislav Nikolov , Nenad Tomasev , Samuel Blackwell , Harry Askham , Xavier Glorot , Balaji Lakshminarayanan , Trevor Back , Mustafa Suleyman , Pearse A. Keane , Olaf Ronneberger , Julien Robert Michel Cornebise
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final classification output for an image of eye tissue. The image is provided as input to each of one or more segmentation neural networks to obtain one or more segmentation maps of the eye tissue in the image. A respective classification input is generated from each of the segmentation maps. For each of the segmentation maps, the classification input for the segmentation map is provided as input to each of one or more classification neural networks to obtain, for each segmentation map, a respective classification output from each classification neural network. A final classification output for the image is generated from the respective classification outputs for each of the segmentation maps.
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公开(公告)号：US11507827B2
公开(公告)日：2022-11-22
申请号：US16601455
申请日：2019-10-14
Applicant: DeepMind Technologies Limited
Inventor： Praveen Deepak Srinivasan , Rory Fearon , Cagdas Alcicek , Arun Sarath Nair , Samuel Blackwell , Vedavyas Panneershelvam , Alessandro De Maria , Volodymyr Mnih , Koray Kavukcuoglu , David Silver , Mustafa Suleyman
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributed training of reinforcement learning systems. One of the methods includes receiving, by a learner, current values of the parameters of the Q network from a parameter server, wherein each learner maintains a respective learner Q network replica and a respective target Q network replica; updating, by the learner, the parameters of the learner Q network replica maintained by the learner using the current values; selecting, by the learner, an experience tuple from a respective replay memory; computing, by the learner, a gradient from the experience tuple using the learner Q network replica maintained by the learner and the target Q network replica maintained by the learner; and providing, by the learner, the computed gradient to the parameter server.
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公开(公告)号：US10445641B2
公开(公告)日：2019-10-15
申请号：US15016173
申请日：2016-02-04
Applicant: DeepMind Technologies Limited
Inventor： Praveen Deepak Srinivasan , Rory Fearon , Cagdas Alcicek , Arun Sarath Nair , Samuel Blackwell , Vedavyas Panneershelvam , Alessandro De Maria , Volodymyr Mnih , Koray Kavukcuoglu , David Silver , Mustafa Suleyman
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for distributed training of reinforcement learning systems. One of the methods includes receiving, by a learner, current values of the parameters of the Q network from a parameter server, wherein each learner maintains a respective learner Q network replica and a respective target Q network replica; updating, by the learner, the parameters of the learner Q network replica maintained by the learner using the current values; selecting, by the learner, an experience tuple from a respective replay memory; computing, by the learner, a gradient from the experience tuple using the learner Q network replica maintained by the learner and the target Q network replica maintained by the learner; and providing, by the learner, the computed gradient to the parameter server.
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6.发明申请公开(公告)号：US20190005684A1
公开(公告)日：2019-01-03
申请号：US16022170
申请日：2018-06-28
Applicant: DeepMind Technologies Limited
Inventor： Jeffrey De Fauw , Joseph R. Ledsam , Bernardino Romera-Paredes , Stanislav Nikolov , Nenad Tomasev , Samuel Blackwell , Harry Askham , Xavier Glorot , Balaji Lakshminarayanan , Trevor Back , Mustafa Suleyman , Pearse A. Keane , Olaf Ronneberger , Julien Robert Michel Cornebise
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a final classification output for an image of eye tissue. The image is provided as input to each of one or more segmentation neural networks to obtain one or more segmentation maps of the eye tissue in the image. A respective classification input is generated from each of the segmentation maps. For each of the segmentation maps, the classification input for the segmentation map is provided as input to each of one or more classification neural networks to obtain, for each segmentation map, a respective classification output from each classification neural network. A final classification output for the image is generated from the respective classification outputs for each of the segmentation maps.
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