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    System and method for generating training cases for image classification
    1.
    发明授权
    System and method for generating training cases for image classification 有权
    用于生成图像分类训练样本的系统和方法

    公开(公告)号：US09251437B2

    公开(公告)日：2016-02-02

    申请号：US13970869

    申请日：2013-08-20

    Applicant: Google Inc.

    Inventor： Alexander Krizhevsky ,  Ilya Sutskever ,  Geoffrey E. Hinton

    IPC: G06K9/62

    CPC classification number: G06K9/6255

    Abstract: A system and method for generating training images. An existing training image is associated with a classification. The system includes an image processing module that performs color-space deformation on each pixel of the existing training image and then associates the classification to the color-space deformed training image. The technique may be applied to increase the size of a training set for training a neural network.

    Abstract translation: 一种用于生成训练图像的系统和方法。 现有的训练图像与分类相关联。 该系统包括图像处理模块，其在现有训练图像的每个像素上执行颜色空间变形，然后将分类与颜色空间变形的训练图像相关联。 该技术可以用于增加用于训练神经网络的训练集的大小。

    SYSTEM AND METHOD FOR GENERATING TRAINING CASES FOR IMAGE CLASSIFICATION
    2.
    发明申请
    SYSTEM AND METHOD FOR GENERATING TRAINING CASES FOR IMAGE CLASSIFICATION 有权
    用于生成图像分类培训案例的系统和方法

    公开(公告)号：US20140177947A1

    公开(公告)日：2014-06-26

    申请号：US13970869

    申请日：2013-08-20

    Applicant: Google Inc.

    Inventor： Alexander Krizhevsky ,  Ilya Sutskever ,  Geoffrey E. Hinton

    IPC: G06K9/62

    CPC classification number: G06K9/6255

    Abstract: A system and method for generating training images. An existing training image is associated with a classification. The system includes an image processing module that performs color-space deformation on each pixel of the existing training image and then associates the classification to the color-space deformed training image. The technique may be applied to increase the size of a training set for training a neural network.

    Abstract translation: 一种用于生成训练图像的系统和方法。 现有的训练图像与分类相关联。 该系统包括图像处理模块，其在现有训练图像的每个像素上执行颜色空间变形，然后将分类与颜色空间变形的训练图像相关联。 该技术可以用于增加用于训练神经网络的训练集的大小。

    System and method for addressing overfitting in a neural network
    7.
    发明授权
    System and method for addressing overfitting in a neural network 有权
    用于解决神经网络过拟合的系统和方法

    公开(公告)号：US09406017B2

    公开(公告)日：2016-08-02

    申请号：US14015768

    申请日：2013-08-30

    Applicant: Google Inc.

    Inventor： Geoffrey E. Hinton ,  Alexander Krizhevsky ,  Ilya Sutskever ,  Nitish Srivastva

    IPC: G06N3/08 ,  G06N3/04

    CPC classification number: G06N3/084 ,  G06K9/4628 ,  G06N3/0454 ,  G06N3/0472 ,  G06N3/082

    Abstract: A system for training a neural network. A switch is linked to feature detectors in at least some of the layers of the neural network. For each training case, the switch randomly selectively disables each of the feature detectors in accordance with a preconfigured probability. The weights from each training case are then normalized for applying the neural network to test data.

    Abstract translation: 用于训练神经网络的系统。 开关被连接到神经网络的至少一些层中的特征检测器。 对于每个训练情况，交换机根据预配置的概率随机选择性地禁用每个特征检测器。 然后对每个训练情况的权重进行归一化，以将神经网络应用于测试数据。

    PARALLELIZING THE TRAINING OF CONVOLUTIONAL NEURAL NETWORKS
    8.
    发明申请
    PARALLELIZING THE TRAINING OF CONVOLUTIONAL NEURAL NETWORKS 审中-公开
    并行训练神经网络

    公开(公告)号：US20150294219A1

    公开(公告)日：2015-10-15

    申请号：US14684186

    申请日：2015-04-10

    Applicant: Google Inc.

    Inventor： Alexander Krizhevsky

    IPC: G06N3/08 ,  G06N3/04

    CPC classification number: G06N3/084 ,  G06K9/4628 ,  G06N3/0454

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a convolutional neural network (CNN). The system includes a plurality of workers, wherein each worker is configured to maintain a respective replica of each of the convolutional layers of the CNN and a respective disjoint partition of each of the fully-connected layers of the CNN, wherein each replica of a convolutional layer includes all of the nodes in the convolutional layer, and wherein each disjoint partition of a fully-connected layer includes a portion of the nodes of the fully-connected layer.

    Abstract translation: 方法，系统和装置，包括在计算机存储介质上编码的用于训练卷积神经网络（CNN）的计算机程序。 该系统包括多个工作人员，其中每个工作人员被配置为维护CNN的每个卷积层的相应副本以及CNN的每个完全连接的层的相应不相交的分区，其中卷积卷积的每个副本 层包括卷积层中的所有节点，并且其中完全连接层的每个不相交分区包括完全连接层的节点的一部分。

    SYSTEM AND METHOD FOR ADDRESSING OVERFITTING IN A NEURAL NETWORK
    9.
    发明申请
    SYSTEM AND METHOD FOR ADDRESSING OVERFITTING IN A NEURAL NETWORK 审中-公开
    用于解决神经网络覆盖的系统和方法

    公开(公告)号：US20160335540A1

    公开(公告)日：2016-11-17

    申请号：US15222870

    申请日：2016-07-28

    Applicant: Google Inc.

    Inventor： Geoffrey E. Hinton ,  Alexander Krizhevsky ,  Ilya Sutskever ,  Nitish Srivastva

    IPC: G06N3/08 ,  G06N3/04

    CPC classification number: G06N3/084 ,  G06K9/4628 ,  G06N3/0454 ,  G06N3/0472 ,  G06N3/082

    Abstract: A system for training a neural network. A switch is linked to feature detectors in at least some of the layers of the neural network. For each training case, the switch randomly selectively disables each of the feature detectors in accordance with a preconfigured probability. The weights from each training case are then normalized for applying the neural network to test data.

    Abstract translation: 用于训练神经网络的系统。 开关被连接到神经网络的至少一些层中的特征检测器。 对于每个训练情况，交换机根据预配置的概率随机选择性地禁用每个特征检测器。 然后对每个训练情况的权重进行归一化，以将神经网络应用于测试数据。

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